From 4762f7803d9160cd0fed1d94b810db8bceb2ed41 Mon Sep 17 00:00:00 2001 From: joshwlambert Date: Thu, 27 Jun 2024 15:21:27 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20epiverse?= =?UTF-8?q?-trace/epiparameter@6d8677d2132f994ceca521288a6d0dc2e7aadfe8=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- LICENSE-text.html | 4 ++ articles/extract-bias.html | 32 ++++++----- index.html | 80 ++++++++++++++++++++++------ news/index.html | 27 ++++++++++ pkgdown.yml | 2 +- reference/as_epidist.data.frame.html | 6 --- reference/new_epidist.html | 29 ---------- search.json | 2 +- 8 files changed, 112 insertions(+), 70 deletions(-) diff --git a/LICENSE-text.html b/LICENSE-text.html index ad9d53df6..3145b40b7 100644 --- a/LICENSE-text.html +++ b/LICENSE-text.html @@ -75,6 +75,10 @@
Developer Documentation
YEAR: 2024
 COPYRIGHT HOLDER: epiparameter authors
+DATA LICENSE: All data included in the epiparameter R package is licensed under CC0
+            (https://creativecommons.org/publicdomain/zero/1.0/legalcode.txt). This includes the parameter
+            database (extdata/parameters.json) and data in the data/ folder. Please cite the individual
+            parameter entries in the database when used.
diff --git a/articles/extract-bias.html b/articles/extract-bias.html index 9c9c1b838..cd89d6568 100644 --- a/articles/extract-bias.html +++ b/articles/extract-bias.html @@ -250,8 +250,7 @@

Extraction by percentiles theme( strip.background = element_blank(), axis.text.x = element_text(angle = 30, vjust = 0.5) - ) -#> Warning in vp$just: partial match of 'just' to 'justification' + )
Parameter estimation bias facetted by distribution. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
Parameter estimation bias facetted by distribution. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
@@ -334,8 +333,9 @@

Extraction by median and range) } #> Warning: Maximum optimisation iterations reached, returning result early. -#> Result may not be reliable. - +#> Result may not be reliable. +
Code
+
 # combine results
 results <- cbind(parameters_range, do.call(rbind, estim_params))
 
@@ -350,7 +350,7 @@ 
Extraction by median and range= abs(results$param_2 - results$estim_param_2)
 )

Plot results:

-
Code
+
Code
 # plot differences by distribution
 ggplot(data = results) +
   geom_point(
@@ -369,8 +369,7 @@ 
Extraction by median and rangetheme(
     strip.background = element_blank(),
     axis.text.x = element_text(angle = 30, vjust = 0.5)
-  )
-#> Warning in vp$just: partial match of 'just' to 'justification'

+  )
Parameter extraction bias. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
Parameter extraction bias. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
@@ -390,7 +389,7 @@

Extraction by percentilesWe use the same parameter space for percentiles as defined above (parameters_perc). Now we can run the extraction for a set of replicates to compute the variance of parameter estimates over those replicates.

-
Code
+
Code
 estim_param_var <- vector("list", nrow(parameters_perc))
 # Loop through parameter space estimating parameters
 for (params_idx in seq_len(nrow(parameters_perc))) {
@@ -439,7 +438,7 @@ 
Extraction by percentiles  "dist", "param_1", "param_2", "lower", "upper",
   "deg_asym", "estim_param_1_var", "estim_param_2_var"
 )

-
Code
Code
 ggplot(data = results) +
   geom_point(mapping = aes(
     x = estim_param_1_var,
@@ -455,8 +454,7 @@ 
Extraction by percentiles  theme(
     strip.background = element_blank(),
     axis.text.x = element_text(angle = 30, vjust = 0.5)
-  )
-#> Warning in vp$just: partial match of 'just' to 'justification'

+  )
Parameter extraction precision, facetted by distribution. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
Parameter extraction precision, facetted by distribution. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
@@ -465,7 +463,7 @@

Extraction by percentilesExtraction by median and range

The same test of estimation precision can be performed for the extraction from median and range.

-
Code
+
Code
 estim_param_var <- vector("list", nrow(parameters_range))
 # Loop through parameter space estimating parameters
 for (params_idx in seq_len(nrow(parameters_range))) {
@@ -532,8 +530,9 @@ 
Extraction by median and range  estim_param_var[[params_idx]] <- apply(estim, MARGIN = 1, FUN = var)
 }
 #> Warning: Maximum optimisation iterations reached, returning result early. 
-#> Result may not be reliable.
-
+#> Result may not be reliable.

+
Code
+
 # combine results
 results <- cbind(parameters_range, do.call(rbind, estim_param_var))
 
@@ -541,7 +540,7 @@ 
Extraction by median and range  "dist", "param_1", "param_2", "n_samples", "estim_param_1_var",
   "estim_param_2_var"
 )

-
Code
Code
 ggplot(data = results) +
   geom_point(mapping = aes(
     x = estim_param_1_var,
@@ -557,8 +556,7 @@ 
Extraction by median and range  theme(
     strip.background = element_blank(),
     axis.text.x = element_text(angle = 30, vjust = 0.5)
-  )
-#> Warning in vp$just: partial match of 'just' to 'justification'

+  )
Parameter extraction precision, facetted by distribution. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
Parameter extraction precision, facetted by distribution. Parameter 1 is either the shape parameter, for gamma and Weibull distributions, or meanlog for the lognormal distribution. Parameter 2 is either the scale parameter for gamma and Weibull distributions, or sdlog for the lognormal distribution.
diff --git a/index.html b/index.html index 8d17dc804..4acbbda4d 100644 --- a/index.html +++ b/index.html @@ -113,29 +113,77 @@

Installation# check whether {pak} is installed if(!require("pak")) install.packages("pak") pak::pak("epiverse-trace/epiparameter") +

Alternatively, install pre-compiled binaries from the Epiverse TRACE R-universe

+
+install.packages("epiparameter", repos = c("https://epiverse-trace.r-universe.dev", "https://cloud.r-project.org"))

Quick start

-
+
 
To load the library of epidemiological parameters into R:

-
+
 epidists <- epidist_db()
 #> Returning 122 results that match the criteria (99 are parameterised). 
 #> Use subset to filter by entry variables or single_epidist to return a single entry. 
 #> To retrieve the citation for each use the 'get_citation' function

-
+
 epidists
-#> List of <epidist> objects
-#>   Number of entries in library: 122
-#>   Number of studies in library: 47
-#>   Number of diseases: 23
-#>   Number of delay distributions: 112
-#>   Number of offspring distributions: 10

+#> # List of 122 <epidist> objects
+#> Number of diseases: 23
+#> ❯ Adenovirus ❯ Chikungunya ❯ COVID-19 ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ Marburg Virus Disease ❯ Measles ❯ MERS ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ Rhinovirus ❯ Rift Valley Fever ❯ RSV ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease
+#> Number of epi distributions: 12
+#> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval
+#> [[1]]
+#> Disease: Adenovirus
+#> Pathogen: Adenovirus
+#> Epi Distribution: incubation period
+#> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009).
+#> "Incubation periods of acute respiratory viral infections: a systematic
+#> review." _The Lancet Infectious Diseases_.
+#> doi:10.1016/S1473-3099(09)70069-6
+#> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>.
+#> Distribution: lnorm
+#> Parameters:
+#>   meanlog: 1.247
+#>   sdlog: 0.975
+#> 
+#> [[2]]
+#> Disease: Human Coronavirus
+#> Pathogen: Human_Cov
+#> Epi Distribution: incubation period
+#> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009).
+#> "Incubation periods of acute respiratory viral infections: a systematic
+#> review." _The Lancet Infectious Diseases_.
+#> doi:10.1016/S1473-3099(09)70069-7
+#> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>.
+#> Distribution: lnorm
+#> Parameters:
+#>   meanlog: 0.742
+#>   sdlog: 0.918
+#> 
+#> [[3]]
+#> Disease: SARS
+#> Pathogen: SARS-Cov-1
+#> Epi Distribution: incubation period
+#> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009).
+#> "Incubation periods of acute respiratory viral infections: a systematic
+#> review." _The Lancet Infectious Diseases_.
+#> doi:10.1016/S1473-3099(09)70069-8
+#> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>.
+#> Distribution: lnorm
+#> Parameters:
+#>   meanlog: 0.660
+#>   sdlog: 1.205
+#> 
+#> # ℹ 119 more elements
+#> # ℹ Use `print(n = ...)` to see more elements.
+#> # ℹ Use `parameter_tbl()` to see a summary table of the parameters.
+#> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html

 
This results a list of database entries. Each entry of the library is an <epidist> object.

 
The results can be filtered by disease and epidemiological distribution. Here we set single_epidist = TRUE as we only want a single database entry returned, and by default (single_epidist = FALSE) it will return all database entries that match the disease (disease) and epidemiological distribution (epi_dist).

-
+
-
+
 
To quickly view the list of epidemiological distributions returned by epidist_db() in a table, the parameter_tbl() gives a summary of the data, and offers the ability to subset you data by disease, pathogen and epidemiological distribution (epi_dist).

-
+
-
+
 
The <epidist> object can be plotted.

-
+
 plot(influenza_incubation)

 

 
The CDF can also be plotted by setting cumulative = TRUE.

-
+
 plot(influenza_incubation, cumulative = TRUE)

 

 

@@ -246,7 +294,7 @@ 
Code of Conduct
 
Citing this package
 

-
+
 citation("epiparameter")
 #> To cite package 'epiparameter' in publications use:
 #> 
diff --git a/news/index.html b/news/index.html
index 4a664f809..f0c948716 100644
--- a/news/index.html
+++ b/news/index.html
@@ -75,6 +75,33 @@ 
Developer Documentation

 
     

 
epiparameter (development version)

+
The second release of the {epiparameter} R package focuses on interoperability with the {epireview} R package. Several functions have been refactored and enhanced.

+

+
New features

+
  • The as_epidist() S3 generic has been added to the package for the coercion of other R objects into <epidist> objects. The as_epidist.data.frame() method is added, as well as the internal functions is_epireview() which determines if a <data.frame> is from {epireview}, and epireview_to_epidist() performs the conversion (#298, #334 & #335)
    • 
+
  • The epireview_core_cols.rda data is added to the package. This is used to determine whether the input to as_epidist.data.frame() is a parameter table from {epireview} as these objects do not have a recognisable class attribute (#298).
    • 
+
  • A new website only vignette (i.e. article) data_from_epireview.Rmd is added that explains how to use as_epidist() with data from {epireview} (#298 & #335).
    • 
+
  • A new vignette database.Rmd is added to the package to provide a web interface to the {epiparameter} library of epidemiological parameters. Contributed by @sbfnk (#311).
    • 
+
  • The plotting method for <epidist> objects (plot.epidist()) has been improved to better differentiate continuous from discrete or discretised distributions (#315).
    • 
+
  • epidist_db(..., single_epidist = TRUE) now prioritises parameter entries that account for right truncation (#323).
    • 
+
  • create_epidist_prob_dist() (previously named create_prob_dist()) is now exported and enables more control of discretisation settings by allowing arguments to be passed to distcrete::distcrete() via ... (#324).
    • 
+
  • The <multi_epidist> print method (print.multi_epidist()) has been improved to provides object information in the print header, the first few elements of the list or all elements if list is short, and some extra links and advice in the print footer. The design of the print method follows the design pattern of {pillar} (#326).
    • 
+
  • <epidist> objects and functions that work with <epidist> objects now work with exponential distributions (#333).
    • 
+
  • The package now has an explicit data license: CC0 in the LICENSE file.
    • 
+

+

+
Breaking changes

+
  • list_distributions() has been replaced by parameter_tbl() which enhances the printing by leveraging {pillar} (#321).
    • 
+
  • The <vb_epidist> plotting method (plot.vb_epidist()) has been removed from the package. This provided minimal functionality and was unnecessarily complicating the function signature of plot.epidist() (#315).
    • 
+

+

+
Bug fixes

+
  • DOI and PMID are lowercase throughout the package to resolve issues with older versions of R (see issue #301) (#317).
    • 
+

+

+
Deprecated and defunct

+
  • None
    • 
+

 

     

 
epiparameter 0.1.0

diff --git a/pkgdown.yml b/pkgdown.yml
index 4540407cf..4bd42fe22 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -9,7 +9,7 @@ articles:
   epiparameter: epiparameter.html
   extract_convert: extract_convert.html
   extract-bias: extract-bias.html
-last_built: 2024-06-26T17:32Z
+last_built: 2024-06-27T15:20Z
 urls:
   reference: https://epiverse-trace.github.io/epiparameter/reference
   article: https://epiverse-trace.github.io/epiparameter/articles
diff --git a/reference/as_epidist.data.frame.html b/reference/as_epidist.data.frame.html
index 05d0dd2d5..85d848a04 100644
--- a/reference/as_epidist.data.frame.html
+++ b/reference/as_epidist.data.frame.html
@@ -107,12 +107,6 @@ 
Value
An <epidist> object or list of <epidist> objects.

     

 
-    

-    
Examples

-    
# stub
-
-

-    

   

 
diff --git a/reference/new_epidist.html b/reference/new_epidist.html
index dc47d746f..919c50967 100644
--- a/reference/new_epidist.html
+++ b/reference/new_epidist.html
@@ -228,35 +228,6 @@ 
Value
An <epidist> object.

     

 
-    

-    
Examples

-    
epiparameter:::new_epidist(
-  disease = "ebola",
-  pathogen = "ebola_virus",
-  epi_dist = "incubation_period",
-  prob_dist = "gamma",
-  prob_dist_params = c(shape = 1, scale = 1),
-  uncertainty = create_epidist_uncertainty(),
-  summary_stats = create_epidist_summary_stats(),
-  auto_calc_params = TRUE,
-  citation = create_epidist_citation(),
-  metadata = create_epidist_metadata(),
-  method_assess = create_epidist_method_assess(),
-  discretise = FALSE,
-  truncation = NA,
-  notes = "No notes"
-)
-#> Citation cannot be created as author, year, journal or title is missing
-#> Disease: ebola
-#> Pathogen: ebola_virus
-#> Epi Distribution: incubation period
-#> Study: (????). “No citation.”
-#> Distribution: gamma
-#> Parameters:
-#>   shape: 1.000
-#>   scale: 1.000
-

-    

   

 
diff --git a/search.json b/search.json
index 45337de1f..a3a113b77 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://epiverse-trace.github.io/epiparameter/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 epiparameter authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"converting-from-epireview-entries-into-an-epidist-object","dir":"Articles","previous_headings":"","what":"Converting from {epireview} entries into an  object","title":"Using {epireview} with {epiparameter}","text":"{epireview} package nicely provides epidemiological parameter data systematically reviewing literature, {epiparameter} provides custom data structures working epidemiological data R. Therefore, reading data {epireview} R package converting  object hopefully provide greatest utility applied outbreak analytics. start simple example reading Marburg data {epireview} converting  object using as_epidist() function {epiparameter} package. loads list four tables, specifically tibbles, contain bibliographic information ($articles), epidemiological parameters ($params), epidemiological models ($models), outbreak information ($outbreaks). start just using epidemiological parameter table convert information . Given currently delay distributions supported conversion (feature still active development) filter include . select second entry, incubation period, use first example: can simply pass epidemiological parameter set as_epidist() conversion. resulting  contain parameterised probability distribution, instead contains range incubation period ($summary_stats), $metadata shows single case South Africa.","code":"marburg_data <- load_epidata(\"marburg\") #> Warning in pretty_article_label(articles, mark_multiple): There are 1 articles #> with missing first author surname. #> Warning in pretty_article_label(articles, mark_multiple): There are 1 articles #> with missing first author surname and first author first name. #> Warning in pretty_article_label(articles, mark_multiple): There are 1 articles #> with missing year of publication. #> Data loaded for marburg names(marburg_data) #> [1] \"articles\"  \"params\"    \"models\"    \"outbreaks\" marburg_params <- marburg_data$params delay_dist_rows <- grepl(   pattern = \"Human delay\",   x = marburg_params$parameter_type,   fixed = TRUE ) marburg_params <- marburg_params[delay_dist_rows, ] marburg_params #> # A tibble: 14 × 59 #>    parameter_data_id    article_id parameter_type parameter_value parameter_unit #>                                                         #>  1 ace3e3fc6f40bef6da4…          6 Human delay -…             4   Days           #>  2 c2a35e68034b7258065…          6 Human delay -…            NA   Days           #>  3 cef9471d52ca35358d7…          6 Human delay -…             9   Days           #>  4 0106582cf5ed3c52d5e…         20 Human delay -…            NA   Days           #>  5 056a8d6b5f9aee3622d…         27 Human delay -…             9   Days           #>  6 ce3976e2e15df3f6fb9…         27 Human delay -…             5.4 Days           #>  7 3bf73665fa67a6ba7f7…         27 Human delay -…             7   Days           #>  8 ba019f18acac9c5b0b7…         27 Human delay -…             9.3 Days           #>  9 71798b4154011dcd008…         27 Human delay -…             9   Days           #> 10 b91f018b5ca72c9293d…         42 Human delay -…             9   Days           #> 11 e95844c29c00b70dee0…         42 Human delay -…             4   Days           #> 12 415a27bceff2afce958…         42 Human delay -…            22   Days           #> 13 7ce1ea4e35a494de06a…         42 Human delay -…            14.3 Days           #> 14 0eb36537ee9159b12d2…         57 Human delay -…             4.5 Days           #> # ℹ 54 more variables: parameter_lower_bound , #> #   parameter_upper_bound , parameter_value_type , #> #   parameter_uncertainty_single_value , #> #   parameter_uncertainty_singe_type , #> #   parameter_uncertainty_lower_value , #> #   parameter_uncertainty_upper_value , parameter_uncertainty_type , #> #   cfr_ifr_numerator , cfr_ifr_denominator , … marburg_incub <- marburg_params[2, ] marburg_incub #> # A tibble: 1 × 59 #>   parameter_data_id     article_id parameter_type parameter_value parameter_unit #>                                                         #> 1 c2a35e68034b72580654…          6 Human delay -…              NA Days           #> # ℹ 54 more variables: parameter_lower_bound , #> #   parameter_upper_bound , parameter_value_type , #> #   parameter_uncertainty_single_value , #> #   parameter_uncertainty_singe_type , #> #   parameter_uncertainty_lower_value , #> #   parameter_uncertainty_upper_value , parameter_uncertainty_type , #> #   cfr_ifr_numerator , cfr_ifr_denominator , … marburg_incub_epidist <- as_epidist(marburg_incub) #> Using Gear (1975). \".\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object marburg_incub_epidist #> Disease: Marburg Virus Disease #> Pathogen: Marburg virus #> Epi Distribution: human delay   incubation period #> Study: Gear (1975). \"<title not available>.\" _<journal not available>_. #> Distribution: NA marburg_incub_epidist$summary_stats #> $mean #> [1] NA #>  #> $mean_ci_limits #> [1] NA NA #>  #> $mean_ci #> [1] NA #>  #> $sd #> [1] NA #>  #> $sd_ci_limits #> [1] NA NA #>  #> $sd_ci #> [1] NA #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] 7 8 marburg_incub_epidist$metadata #> $sample_size #> [1] 1 #>  #> $region #> [1] \"Johannesburg, South Africa\" #>  #> $transmission_mode #> [1] NA #>  #> $vector #> [1] NA #>  #> $extrinsic #> [1] FALSE #>  #> $inference_method #> [1] NA"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"creating-an-epidist-with-full-citation","dir":"Articles","previous_headings":"","what":"Creating an <epidist> with full citation","title":"Using {epireview} with {epiparameter}","text":"last example showed convert epidemiological parameter information, however, may noticed citation created contain information full citation. order provide complete citation <epidist> object, highly recommended know provenance parameters can correctly attribute original authors, need also provide bibliographic information {epireview} well epidemiological parameters. article data needs loaded {epireview} using epireview::load_epidata_raw() rather epireview::load_data() load_data() subsets bibliographic information provide: \"id\", \"first_author_surname\", \"year_publication\", \"article_label\" columns. need match entry epidemiological parameter table citation information article table ensure using correct citation parameter set. Thankfully, can easily achieved {epireview} provides unique IDs table link entries. Now can repeat example converting <epidist> shown , time pass bibliographic information well epidemiological parameter information create full citation. bibliographic information needs passed articles argument. as_epidist() function S3 generic. familiar S3 object-oriented programming R, detail important, however, mean articles argument explicitly function definition as_epidist() (.e. show autocomplete typing function shown read function help page ?as_epidist()). Instead, argument specified part ... argument. articles argument required converting data {epireview} <epidist>, data can converted <epidist> objects require argument.","code":"marburg_incub_epidist$citation #> Gear (1975). \"<title not available>.\" _<journal not available>_. marburg_articles <- load_epidata_raw(   pathogen = \"marburg\",   table = \"article\" ) marburg_articles #> # A tibble: 58 × 25 #>    article_id pathogen   covidence_id first_author_first_n…¹ article_title doi   #>         <dbl> <chr>             <int> <chr>                  <chr>         <chr> #>  1          1 Marburg v…         2059 G A                    Haemorrhagic… NA    #>  2          2 Marburg v…         2042 Christian              Antibodies t… NA    #>  3          3 Marburg v…         1649 Y                      The origin a… 10.1… #>  4          4 Marburg v…         1692 D.H.                   Marburg-Viru… NA    #>  5          5 Marburg v…         2597 E. D.                  Filovirus ac… NA    #>  6          6 Marburg v…         3795 JS                     Outbreak of … 10.1… #>  7          7 Marburg v…         2596 E.D.                   Haemorrhagic… NA    #>  8          8 Marburg v…         1615 O                      Viral hemorr… 10.4… #>  9          9 Marburg v…         1693 Smiley                 Suspected Ex… 10.1… #> 10         10 Marburg v…         1692 D                      Marburg-viru… NA    #> # ℹ 48 more rows #> # ℹ abbreviated name: ¹​first_author_first_name #> # ℹ 19 more variables: journal <chr>, year_publication <int>, volume <int>, #> #   issue <int>, page_first <int>, page_last <int>, paper_copy_only <lgl>, #> #   notes <chr>, first_author_surname <chr>, double_extracted <dbl>, #> #   qa_m1 <int>, qa_m2 <int>, qa_a3 <int>, qa_a4 <int>, qa_d5 <int>, #> #   qa_d6 <int>, qa_d7 <int>, score <dbl>, id <chr> article_row <- match(marburg_incub$id, marburg_articles$id) article_row #> [1] 6 marburg_incub_article <- marburg_articles[article_row, ] marburg_incub_article #> # A tibble: 1 × 25 #>   article_id pathogen    covidence_id first_author_first_n…¹ article_title doi   #>        <dbl> <chr>              <int> <chr>                  <chr>         <chr> #> 1          6 Marburg vi…         3795 JS                     Outbreak of … 10.1… #> # ℹ abbreviated name: ¹​first_author_first_name #> # ℹ 19 more variables: journal <chr>, year_publication <int>, volume <int>, #> #   issue <int>, page_first <int>, page_last <int>, paper_copy_only <lgl>, #> #   notes <chr>, first_author_surname <chr>, double_extracted <dbl>, #> #   qa_m1 <int>, qa_m2 <int>, qa_a3 <int>, qa_a4 <int>, qa_d5 <int>, #> #   qa_d6 <int>, qa_d7 <int>, score <dbl>, id <chr> marburg_incub_epidist <- as_epidist(   marburg_incub,   articles = marburg_incub_article ) #> Using Gear (1975). \"Outbreak of Marburg virus disease in Johannesburg.\" _The #> British Medical Journal_. doi:10.1136/bmj.4.5995.489 #> <https://doi.org/10.1136/bmj.4.5995.489>.  #> To retrieve the citation use the 'get_citation' function #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object marburg_incub_epidist #> Disease: Marburg Virus Disease #> Pathogen: Marburg virus #> Epi Distribution: human delay   incubation period #> Study: Gear (1975). \"Outbreak of Marburg virus disease in Johannesburg.\" _The #> British Medical Journal_. doi:10.1136/bmj.4.5995.489 #> <https://doi.org/10.1136/bmj.4.5995.489>. #> Distribution: NA marburg_incub_epidist$citation #> Gear (1975). \"Outbreak of Marburg virus disease in Johannesburg.\" _The #> British Medical Journal_. doi:10.1136/bmj.4.5995.489 #> <https://doi.org/10.1136/bmj.4.5995.489>."},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"multi-row-epireview-entries","dir":"Articles","previous_headings":"","what":"Multi-row {epireview} entries","title":"Using {epireview} with {epiparameter}","text":"way {epireview} data stored means epidemiological parameter entries require multiple rows. can , example, contain two summary statistics (e.g. mean standard deviation) kept separate rows. order create <epidist> objects contains full information entry multiple rows epidemiological parameters table {epireview} can given as_epidist() create single <epidist> object. can search data entries multiple rows checking duplicated parameter types IDs. Remembering using delay distributions (.e. Human delay) epidemiological parameters, subset . step verified manually ensure entries selected indeed multiple rows reported epidemiological parameter. use first two rows subset table, mean standard deviation generation time Marburg disease. can now convert <epidist>.","code":"multi_row_entries <- duplicated(marburg_params$parameter_type) &   duplicated(marburg_params$id) multi_row_ids <- marburg_params$id[multi_row_entries] multi_row_marburg_params <-   marburg_params[marburg_params$id %in% multi_row_ids, ] marburg_gt <- multi_row_marburg_params[1:2, ] marburg_gt_epidist <- as_epidist(marburg_gt) #> Using Ajelli (2012). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object marburg_gt_epidist #> Disease: Marburg Virus Disease #> Pathogen: Marburg virus #> Epi Distribution: human delay   generation time #> Study: Ajelli (2012). \"<title not available>.\" _<journal not available>_. #> Distribution: NA marburg_gt_epidist$summary_stats #> $mean #> [1] 9 #>  #> $mean_ci_limits #> [1]  8.2 10.0 #>  #> $mean_ci #> [1] 95 #>  #> $sd #> [1] 5.4 #>  #> $sd_ci_limits #> [1] 3.9 8.6 #>  #> $sd_ci #> [1] 95 #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] NA NA"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"entries-with-probability-distributions","dir":"Articles","previous_headings":"","what":"Entries with probability distributions","title":"Using {epireview} with {epiparameter}","text":"example load Ebola epidemiological parameters {epireview} package (entries Marburg parametric distributions). subset data just use epidemiological parameter table, subset table just delay distributions. select 358th entry, serial interval, entry estimated reported Weibull distribution: can now convert <epidist> object. probability distribution serial interval can utilise <epidist> methods. illustrate checking <epidist> parameterised, plotting PDF CDF, generating 10 random numbers sampling distribution.","code":"ebola_data <- load_epidata(\"ebola\") #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata_raw(pathogen, \"outbreak\"): No data found for ebola #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata(\"ebola\"): No outbreaks information found for ebola #> Data loaded for ebola ebola_params <- ebola_data$params delay_dist_rows <- grepl(   pattern = \"Human delay\",   x = ebola_params$parameter_type,   fixed = TRUE ) ebola_params <- ebola_params[delay_dist_rows, ] ebola_params #> # A tibble: 395 × 77 #>    id     parameter_data_id covidence_id pathogen parameter_type parameter_value #>    <chr>  <chr>                    <int> <chr>    <chr>                    <dbl> #>  1 b6168… 6f5cb18602d0dfec…           30 Ebola v… Human delay -…            NA   #>  2 b6168… 55766cedfbf75a9c…           30 Ebola v… Human delay -…            NA   #>  3 0a142… 3ae1f6b55d0f1cc5…           41 Ebola v… Human delay -…             9.2 #>  4 0a142… f0a0191af0663265…           41 Ebola v… Human delay -…             5.8 #>  5 0a142… a83683d0b55750df…           41 Ebola v… Human delay -…            10.6 #>  6 99d84… f4aaae2be84dee6c…           57 Ebola v… Human delay -…             8.6 #>  7 99d84… 1ea610e2489a3257…           57 Ebola v… Human delay -…             4.4 #>  8 99d84… 4316d44cbd32d365…           57 Ebola v… Human delay -…            14.4 #>  9 99d84… 7dfc17eab39f9aa0…           57 Ebola v… Human delay -…             8.6 #> 10 99d84… c9c3fc483d332934…           57 Ebola v… Human delay -…            10.6 #> # ℹ 385 more rows #> # ℹ 71 more variables: exponent <dbl>, parameter_unit <chr>, #> #   parameter_lower_bound <dbl>, parameter_upper_bound <dbl>, #> #   parameter_value_type <chr>, parameter_uncertainty_single_value <dbl>, #> #   parameter_uncertainty_singe_type <chr>, #> #   parameter_uncertainty_lower_value <dbl>, #> #   parameter_uncertainty_upper_value <dbl>, … ebola_si <- ebola_params[358, ] ebola_si #> # A tibble: 1 × 77 #>   id      parameter_data_id covidence_id pathogen parameter_type parameter_value #>   <chr>   <chr>                    <int> <chr>    <chr>                    <dbl> #> 1 b76dcc… 0c3e02f80addfccc…        17730 Ebola v… Human delay -…              12 #> # ℹ 71 more variables: exponent <dbl>, parameter_unit <chr>, #> #   parameter_lower_bound <dbl>, parameter_upper_bound <dbl>, #> #   parameter_value_type <chr>, parameter_uncertainty_single_value <dbl>, #> #   parameter_uncertainty_singe_type <chr>, #> #   parameter_uncertainty_lower_value <dbl>, #> #   parameter_uncertainty_upper_value <dbl>, parameter_uncertainty_type <chr>, #> #   cfr_ifr_numerator <int>, cfr_ifr_denominator <int>, … ebola_si_epidist <- as_epidist(ebola_si) #> Using Marziano (2023). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. ebola_si_epidist #> Disease: Ebola Virus Disease #> Pathogen: Ebola virus #> Epi Distribution: human delay   serial interval #> Study: Marziano (2023). \"<title not available>.\" _<journal not available>_. #> Distribution: weibull #> Parameters: #>   shape: 1.760 #>   scale: 10.140 is_parameterised(ebola_si_epidist) #> [1] TRUE plot(ebola_si_epidist) generate(ebola_si_epidist, times = 10) #>  [1] 17.129838  3.840887  6.913068 14.383495 25.033088  8.693642  8.263781 #>  [8] 11.451308  5.219772  4.697018"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"specifying-the-probability-distribution-if-unknown","dir":"Articles","previous_headings":"","what":"Specifying the probability distribution if unknown","title":"Using {epireview} with {epiparameter}","text":"may instances delay distribution reported, either probability distribution fit data, reported probability distribution parameters correspond . cases, parametric probability distribution required particular epidemiological task assuming probability distribution can useful. Please use feature caution. Assuming incorrect probability distribution applying epidemiological method can lead erroneous results. Additionally, probability distribution specified user overwrite probability distribution specified input data (e.g. {epireview} parameter data) can lead error distribution name supplied parameters input incompatible See ?as_epidist details information. Just example load Ebola parameters using epireview::load_epidata() function subset just parameters ($params). use serial interval Ebola reported Faye et al. (2015). stored, two rows parameter table, mean standard deviation, probability distribution specified. code chunk subsets Ebola parameter table just return serial interval Faye et al. (2015). supply data as_epidist() get unparameterised <epidist> object probability distribution stated. Given can convert mean standard deviation parameters probability distribution assume distribution form, can supply data as_epidist(). Ebola serial interval <epidist> can now used various probability distribution methods.","code":"ebola_data <- load_epidata(\"ebola\") #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata_raw(pathogen, \"outbreak\"): No data found for ebola #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata(\"ebola\"): No outbreaks information found for ebola #> Data loaded for ebola ebola_params <- ebola_data$params ebola_si <- ebola_params[   which(     grepl(pattern = \"Faye\", x = ebola_params$article_label, fixed = TRUE) &       grepl(pattern = \"serial\", ebola_params$parameter_type, fixed = TRUE)   ), ] ebola_si_epidist <- as_epidist(ebola_si) #> Using Faye (2015). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object ebola_si_epidist #> Disease: Ebola Virus Disease #> Pathogen: Ebola virus #> Epi Distribution: human delay   serial interval #> Study: Faye (2015). \"<title not available>.\" _<journal not available>_. #> Distribution: NA is_parameterised(ebola_si_epidist) #> [1] FALSE ebola_si_epidist <- as_epidist(ebola_si, prob_dist = \"gamma\") #> Using Faye (2015). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. ebola_si_epidist #> Disease: Ebola Virus Disease #> Pathogen: Ebola virus #> Epi Distribution: human delay   serial interval #> Study: Faye (2015). \"<title not available>.\" _<journal not available>_. #> Distribution: gamma #> Parameters: #>   shape: 4.000 #>   scale: 3.550 is_parameterised(ebola_si_epidist) #> [1] TRUE get_parameters(ebola_si_epidist) #> shape scale  #>  4.00  3.55 density(ebola_si_epidist, at = 20) #> [1] 0.03001206 plot(ebola_si_epidist) cdf(ebola_si_epidist, q = 10) #> [1] 0.3118251 plot(ebola_si_epidist, cumulative = TRUE) quantile(ebola_si_epidist, p = 0.5) #> [1] 13.03582 generate(ebola_si_epidist, times = 10) #>  [1] 21.222588  3.271134  7.384133 10.618359 15.691544  7.389448  3.953741 #>  [8] 15.905629  7.924347 12.078103"},{"path":[]},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"about-the-package","dir":"Articles","previous_headings":"","what":"About the package","title":"Data Collation and Synthesis Protocol","text":"{epiparameter} R package contains library epidemiological parameter data functions read handle data. delay distributions describe time two events epidemiology, example incubation period, serial interval onset--death; offspring distributions describe number secondary infections primary infection disease transmission. library compiled process collecting, reviewing extracting data peer-reviewed literature1, including research articles, systematic reviews meta-analyses. epiparameter package act ‘living systematic review’ (sensu Elliott et al. (2014)) actively updated maintained provide reliable source data epidemiological distributions. prevent bias collection assessment data, well-defined methodology searching refining required. document aims provide transparency methodology used epiparameter maintainers outlining steps taken stage data handling. can also serve guide contributors wanting search provide epidemiological parameters currently missing library. protocol also facilitate reproducibility searches, results appraisal steps. large body work methods best conduct literature searches data collection part systematic reviews meta-analyses2, use basis protocol. sources : Cochrane Handbook (Higgins et al. 2022) PRISMA (Page et al. 2021)","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"objective-of-epiparameter","dir":"Articles","previous_headings":"","what":"Objective of {epiparameter}","title":"Data Collation and Synthesis Protocol","text":"defined PRISMA guidelines, clearly stated objective helps refine goal project. epiparameter’s objective provide information collection distributions range infectious diseases accurate, unbiased comprehensive possible. distributions enable outbreak analysts easily access distributions routine analysis. example, delay distributions necessary : calculating case fatality rates adjusting delay outcome, quantifying implications different screening measures quarantine periods, estimating reproduction numbers, scenario modelling using transmission dynamic models.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"contributing-to-the-package","dir":"Articles","previous_headings":"","what":"Contributing to the package","title":"Data Collation and Synthesis Protocol","text":"contribute epiparameter library epidemiological parameter information, added data google sheet. integrated epiparameter library package maintainers, information accessible epiparameter package users.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"scope-of-package","dir":"Articles","previous_headings":"","what":"Scope of package","title":"Data Collation and Synthesis Protocol","text":"epiparameter package spans range infectious diseases, including several distributions disease available. pathogens diseases currently systematically searched included package library : distributions currently included literature search pathogen/disease :","code":"#> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-identifying-distributions-in-the-literature","dir":"Articles","previous_headings":"","what":"Guide to identifying distributions in the literature","title":"Data Collation and Synthesis Protocol","text":"Key word searches: searching literature, use specific search phrases ensure correct literature procured required. use search schema includes searching pathogen disease, desired distribution. search phrase can optionally include specific variant/strain/subtype. search constrained based year publication. Examples searches: “SARS-CoV-2 incubation period” “ebola serial interval” “influenza H7N9 onset admission” However, simple search phrases can return large number irrelevant papers. Using specific search schema depending search engine used. example, using Google Scholar schema like: (“Middle East Respiratory Syndrome” MERS) “onset death” (estimation inference calculation) (ebola EVD) “onset death” (estimation inference calculation) Web Science used: (“Middle East Respiratory Syndrome” MERS) “onset death” estimat* (ebola EVD) “onset death” estimat* refine results suitable set literature. Literature search engines: using selection search engines prevent one source potentially omitting papers. Suggested search sites : Google Scholar, Web Science, PubMed, Scopus. Adding papers: addition database entries papers identified literature search, entries can supplemented recommendations (.e. community) cited paper literature search. Papers may recommended experts research public health communities. plan use two methods community engagement. Firstly open-access Google sheet allows people add distribution data reviewed one epiparameter maintainers incorporated meets quality checks. second method - yet implemented - involves community members uploading data zenodo, can read loaded R using epiparameter checked. Language restrictions: papers English Spanish currently supported epiparameter. Papers written another language verified expert can also included database. However, evaluated review process described result flagged user loaded epiparameter.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-data-refinement-once-sources-identified","dir":"Articles","previous_headings":"","what":"Guide to data refinement once sources identified","title":"Data Collation and Synthesis Protocol","text":"Removing duplicates: library parameters contain duplicates studies, multiple entries per study can included paper reports multiple results (e.g. full data set subset data). Studies use data, subsets supersets data used papers library included. Abstract methods screening: number unique sources identified, reviewed suitability reviewing abstract searching words phrases paper indicate reports parameters summary statistics distribution, can include searching methods section words types distributions (e.g. lognormal), fitting procedures (e.g. maximum likelihood bayesian), searching results parameter estimates. epiparameter library includes entries parameters summary statistics reported distribution specified, entries distribution specified parameters reported. database unsuitable papers kept remind maintainers papers included aids updating database (see ) preventing redundant reviewing previously rejected paper. Stopping criteria: many searches, number results far larger reasonably evaluated outside full systematic review. refining papers contain required information (abstract methods screening), around 10 papers per pathogen screened search (per search round, see updating section details). number papers pass abstract methods screening fewer 10, suitable papers reviewed. Full paper screening: abstract methods screening, papers excluded reviewed full verify indeed contain required information distribution parameters information methodology used. acceptable include secondary source contains information delay distribution primary source unavailable report distribution. inference delay distribution primary subject research article, example inferred used estimation \\(R_0\\) can still included database. Additionally, distribution parameters based illustrative values use simulations - rather inferred data - considered unsuitable excluded. , papers excluded stage recorded database unsuitable sources reasoning prevent reassess updating database. Post hoc removal: epiparameter parameters later identified inappropriate can removed database. cases unlikely limitations can appended onto data entries make users aware limitations (e.g. around assumptions used infer distribution), extreme cases data completely removed database. Note: systematic reviews focusing effect sizes can subject publication bias (e.g. positive significant results literature). However, distribution inference focus significance testing effect sizes, bias considered collection process.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-extracting-parameters","dir":"Articles","previous_headings":"","what":"Guide to extracting parameters","title":"Data Collation and Synthesis Protocol","text":"Extracting parameters: underlying distributions (e.g. gamma, lognormal), parameters (e.g. shape/scale, meanlog/sdlog), summary statistics (e.g. mean, standard deviation, median, range quantiles) given paper, values recorded verbatim paper database. read R using epiparameter package, aspects distribution automatically calculated available. example mean standard deviation gamma distribution reported serial interval values stored database. R, shape scale parameters gamma distribution automatically reconstructed resulting distribution available use. epiparameter library exactly reflects literature. mean information present paper imputed prior knowledge (e.g. vector disease known stated), performing calculating reported values. prevents issue clear provenance data library. requirements entry database defined data dictionary. outline minimal dataset required included epiparameter library : Name disease Type distribution Citation information (author(s) paper, year publication, publication title journal, DOI) Whether distribution extrinsic (e.g. extrinsic incubation period). disease vector-borne NA. Whether distribution fitted discretised, boolean (true false). information database entry non-essential. See data dictionary included epiparameter database fields description range possible values field can take.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"data-quality-assessment-in-epiparameter","dir":"Articles","previous_headings":"","what":"Data quality assessment in {epiparameter}","title":"Data Collation and Synthesis Protocol","text":"inference parameters delay distribution often requires methodological adjustments correct factors otherwise bias estimates. includes accounting interval-censoring data timing event (e.g. exposure pathogen) know certainty, rather within time window. adjusting phase bias distribution estimated growing shrinking stage epidemic. aim epiparameter make judgement parameters ‘better’ others, notify warn user potential limitations data. aspects assessed : 1) whether method includes single double interval-censoring exposure onset times known certainty (.e. single day); 2) method adjust phase bias outbreak ascending descending phase. indicated boolean values indicate whether reported paper users recommended refer back paper determine whether estimates biased.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-the-epiparameter-review-process","dir":"Articles","previous_headings":"","what":"Guide to the {epiparameter} review process","title":"Data Collation and Synthesis Protocol","text":"set parameters included database must pass abstract methods screening full screening subsequently review one epiparameter maintainers. process involves running diagnostic checks cross-referencing reported parameters paper ensure match exactly results plot PDF/CDF/PMF matches anything plotted paper, available. prevents possible misinterpretation (e.g. serial interval incubation period). check also includes making sure unique identifiers paper match author’s name, publication year data recorded database.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"updating-parameters-in-the-database","dir":"Articles","previous_headings":"","what":"Updating parameters in the database","title":"Data Collation and Synthesis Protocol","text":"search review stages time consuming continuously carried , aim keep epiparameter library --date living data library conducting regular searches (.e. every 3-4 months) fill missing papers new publication since last search. epidemiological literature can expand rapidly, especially new outbreak. Therefore can optionally include new studies use epidemiological community regular updates. small additions still subject data quality assessment diagnostics ensure accuracy, likely picked subsequent literature searches. likely existing pathogens major increase incidence since last update new papers reporting delay distributions. cases papers previously reviewed due limited reviewing time round updates now checked. particularly value community contributions database, everyone can benefit analysis already conducted, duplicated effort reduced.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"database-of-excluded-papers","dir":"Articles","previous_headings":"","what":"Database of excluded papers","title":"Data Collation and Synthesis Protocol","text":"papers returned search results suitable, either stage abstract screening, reviewing entirety paper, recorded database following information: First author’s last name Unique identifier, ideally DOI Journal, pre-print server, host website One several reasons deemed unsuitable Date recording","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"scope","dir":"Articles","previous_headings":"","what":"Scope","title":"Design Principles for {epiparameter}","text":"{epiparameter} R package library epidemiological parameters, provides class (.e. data structure) helper functions working epidemiological parameters distributions. <epidist> class main functional object working epidemiological parameters can hold information delay distributions (e.g. incubation period, serial interval, onset--death distribution) offspring distributions. class number methods, including allowing user easily calculate PDF, CDF, quantile, generate random numbers, calculate distribution mean, plot distribution. <epidist> object can created constructor function epidist(), uncertain whether object <epidist>, can validated validate_epidist(). package also converts distribution parameters summary statistics, vice versa. achieved either conversion extraction methods functions used explained Parameter extraction conversion {epiparameter} vignette.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"output","dir":"Articles","previous_headings":"","what":"Output","title":"Design Principles for {epiparameter}","text":"output epidist() constructor function <epidist> object. list nine elements, element either single type (e.g. character), non-nested list another class. Classes <epidist> elements used existing well developed infrastructure handling certain data types. $prod_dist element uses distribution class – parameterised distribution available – using either <distribution> class {distributional} <distcrete> class {distcrete}. $citation handled using <bibentry> class {utils} package (included part base R recommended packages). functions return simplest type possible, may atomic vector (including single element vectors), un-nested lists.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"design-decisions","dir":"Articles","previous_headings":"","what":"Design decisions","title":"Design Principles for {epiparameter}","text":"conversion functions (convert_*) S3 generic functions methods provided {epiparameter} character <epidist> input. follows design pattern packages, {dplyr}, export key data transformation functions S3 generics allow developers extend conversions data objects. conversion functions designed single function exported user summary statistics parameters, another function exported parameters summary statistics. functions use switch() dispatch internal conversion functions. provides minimal number conversion functions package namespace compared exporting conversion function every distribution. large number entries returned reading epidemiological parameters library using epidist_db() function, can flood console, due default list printing R. reasoning <multi_epidist> object minimal class enable cleaner descriptive printing large list <epidist> objects. print.multi_epidist() prints header metadata number <epidist> objects number diseases epidemiological distributions list. also lists diseases epidemiological parameters returned. footer print() function states number <epidist> objects shown, guides use print(n = ...) parameter_tbl() link online database vignette (database.Rmd). Information header footer considered metadata advice prefixed #. package uses S3 classes S3 dispatch exported functions, switch() .call() dispatching internal functions. easier develop debug internal functions use S3 dispatch avoids ensure S3 methods registered. Examples S3 dispatch exported functions get_parameters() convert_summary_stats_to_params(). Examples internal dispatch using switch() .call() clean_epidist_params() convert_params_to_summary_stats.character(). function naming convention internal functions dot (.) prefix (e.g. .convert_params_lnorm()).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"dependencies","dir":"Articles","previous_headings":"","what":"Dependencies","title":"Design Principles for {epiparameter}","text":"aim restrict number dependencies minimal required set ease maintenance. current hard dependencies : {checkmate} {distributional} {distcrete} {stats} {utils} {stats} {utils} distributed R language viewed lightweight dependencies, already installed user’s machine R. {checkmate} input checking package widely used across Epiverse-TRACE packages. {distributional} {distcrete} used import S3 classes handling working distributions. required {distcrete} can handle discretised distributions. {jsonlite} suggested dependency used read parameter library stored JSON file. However, read internal function instead data available user via sysdata.rda, {jsonlite} required imported dependency.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"contribute","dir":"Articles","previous_headings":"","what":"Contribute","title":"Design Principles for {epiparameter}","text":"addition package contributing guide, please refer {epiparameter} specific contributing guidelines adding epidemiological parameter package library.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"use-case","dir":"Articles","previous_headings":"","what":"Use case","title":"Getting Started with {epiparameter}","text":"outbreak known potentially novel pathogen detected key parameters delay distributions (e.g. incubation period serial interval) required interpret early data. {epiparameter} can provide distributions selection published sources, past analysis similar pathogen, order provide relevant epidemiological parameters new analysis.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"working-with-epiparameter-data","dir":"Articles","previous_headings":"","what":"Working with {epiparameter} data","title":"Getting Started with {epiparameter}","text":"{epiparameter} introduces two new classes working epidemiological parameters R: <epidist>: Contains name disease, name epidemiological distribution, parameters (available) citation information parameter source, well information. <vb_epidist>: list two <epidist> objects vector-borne disease. One human (intrinsic) distribution, one vector (extrinsic). probability distribution (prob_distribution) argument requires distribution specified standard R naming. cases distribution’s name, e.g., gamma weibull. Examples distribution name R name differ lognormal lnorm, negative binomial nbinom, geometric geom, poisson pois.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"library-of-epidemiological-parameters","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Library of epidemiological parameters","title":"Getting Started with {epiparameter}","text":"First, introduce library, database, epidemiological parameters available {epiparameter}. library stored package JSON file can read R using epidist_db() function. default entries library supplied. output list <epidist> objects, element list corresponds entry parameter database. Technical note: reason object look like regular R list uses custom print method print summary data console 5 entries prevent large list flooding console. number database entries returned less equal 5 print look like standard R list. see full list diseases distributions stored library use parameter_tbl() function. show first six rows output. parameter_tbl() can also subset database supplied function. details data collation library parameters can found Data Collation Synthesis Protocol vignette.","code":"epi_dist_db <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function epi_dist_db #> # List of 122 <epidist> objects #> Number of diseases: 23 #> ❯ Adenovirus ❯ Chikungunya ❯ COVID-19 ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ Marburg Virus Disease ❯ Measles ❯ MERS ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ Rhinovirus ❯ Rift Valley Fever ❯ RSV ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease #> Number of epi distributions: 12 #> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval #> [[1]] #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.247 #>   sdlog: 0.975 #>  #> [[2]] #> Disease: Human Coronavirus #> Pathogen: Human_Cov #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.742 #>   sdlog: 0.918 #>  #> [[3]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.660 #>   sdlog: 1.205 #>  #> # ℹ 119 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html parameter_tbl(multi_epidist = epi_dist_db) #> # Parameter table: #> # A data frame:    122 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 Adenovi… Adenovi… incubation peri… lnorm             Lessl…  2009          14 #>  2 Human C… Human_C… incubation peri… lnorm             Lessl…  2009          13 #>  3 SARS     SARS-Co… incubation peri… lnorm             Lessl…  2009         157 #>  4 Influen… Influen… incubation peri… lnorm             Lessl…  2009         151 #>  5 Influen… Influen… incubation peri… lnorm             Lessl…  2009          90 #>  6 Influen… Influen… incubation peri… lnorm             Lessl…  2009          78 #>  7 Measles  Measles… incubation peri… lnorm             Lessl…  2009          55 #>  8 Parainf… Parainf… incubation peri… lnorm             Lessl…  2009          11 #>  9 RSV      RSV      incubation peri… lnorm             Lessl…  2009          24 #> 10 Rhinovi… Rhinovi… incubation peri… lnorm             Lessl…  2009          28 #> # ℹ 112 more rows parameter_tbl(multi_epidist = epi_dist_db, disease = \"Ebola\") #> # Parameter table: #> # A data frame:    17 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 Ebola V… Ebola V… offspring distr… nbinom            Lloyd…  2005          13 #>  2 Ebola V… Ebola V… incubation peri… lnorm             Eichn…  2011         196 #>  3 Ebola V… Ebola V… onset to death   gamma             The E…  2018          14 #>  4 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015        1798 #>  5 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015          49 #>  6 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015         957 #>  7 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015         792 #>  8 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015         305 #>  9 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015          37 #> 10 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015         147 #> 11 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015         112 #> 12 Ebola V… Ebola V… hospitalisation… gamma             WHO E…  2015        1167 #> 13 Ebola V… Ebola V… hospitalisation… gamma             WHO E…  2015        1004 #> 14 Ebola V… Ebola V… notification to… gamma             WHO E…  2015        2536 #> 15 Ebola V… Ebola V… notification to… gamma             WHO E…  2015        1324 #> 16 Ebola V… Ebola V… onset to death   gamma             WHO E…  2015        2741 #> 17 Ebola V… Ebola V… onset to discha… gamma             WHO E…  2015        1335"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"single-set-of-epidemiological-parameters","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Single set of epidemiological parameters","title":"Getting Started with {epiparameter}","text":"core data structure introduced {epiparameter} package <epidist> class. holds single set epidemiological parameters. <epidist> object can : Pulled database (epidist_db()) Created manually (using class constructor function: epidist()) arguments specified example using class constructor (epidist()) , example metadata parameter uncertainty (uncertainty) provided. See help documentation epidist() function using ?epidist see argument. Also see documentation <epidist> helper functions, e.g., ?create_epidist_citation(). Manually creating <epidist> objects can especially useful new parameter estimates become available yet incorporated {epiparameter} library. seen examples vignette, <epidist> class custom printing method shows disease, pathogen (known), epidemiological distribution, citation study parameters probability distribution parameter distribution (available).","code":"# <epidist> from database  # fetch <epidist> for COVID-19 incubation period from database # return only a single <epidist> covid_incubation <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function covid_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.525 #>   sdlog: 0.629 # <epidist> using constructor function covid_incubation <- epidist(   disease = \"COVID-19\",   pathogen = \"SARS-CoV-2\",   epi_dist = \"incubation period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 2, scale = 1),   summary_stats = create_epidist_summary_stats(mean = 2),   citation = create_epidist_citation(     author = person(       given = list(\"John\", \"Amy\"),       family = list(\"Smith\", \"Jones\")     ),     year = 2022,     title = \"COVID Incubation Period\",     journal = \"Epi Journal\",     doi = \"10.27861182.x\"   ) ) #> Using Smith J, Jones A (2022). \"COVID Incubation Period.\" _Epi Journal_. #> doi:10.27861182.x <https://doi.org/10.27861182.x>.  #> To retrieve the citation use the 'get_citation' function covid_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Smith J, Jones A (2022). \"COVID Incubation Period.\" _Epi Journal_. #> doi:10.27861182.x <https://doi.org/10.27861182.x>. #> Distribution: gamma #> Parameters: #>   shape: 2.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"benefit-of-epidist","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Benefit of <epidist>","title":"Getting Started with {epiparameter}","text":"providing consistent robust object store epidemiological parameters, <epidist> objects can applied epidemiological pipelines, example {episoap}. data contained within object (e.g. parameter values, pathogen type, etc.) can modified pipeline continue operate class unchanged.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"subsetting-database","dir":"Articles","previous_headings":"","what":"Subsetting database","title":"Getting Started with {epiparameter}","text":"database can subset directly epidist_db(). results can subset author. recommended use family name first author instead full name. first author matched entry source multiple authors. results can subset using subset argument, example subset = sample_size > 100 return entries sample size greater 100. See ?epidist_db() details use argument subset database entries get returned.","code":"epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation period\",   author = \"Linton\" ) #> Returning 3 results that match the criteria (3 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function #> # List of 3 <epidist> objects #> Number of diseases: 1 #> ❯ COVID-19 #> Number of epi distributions: 1 #> ❯ incubation period #> [[1]] #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.456 #>   sdlog: 0.555 #>  #> [[2]] #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.611 #>   sdlog: 0.472 #>  #> [[3]] #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.525 #>   sdlog: 0.629 #>  #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"adding-library-entries-and-contributing-to-epiparameter","dir":"Articles","previous_headings":"","what":"Adding library entries and contributing to {epiparameter}","title":"Getting Started with {epiparameter}","text":"set epidemiological parameter inferred known user yet incorporated {epiparameter} database, parameters can manually added library. Note adds parameters library environment, save database file package. library epidemiological parameters living database, new studies published hope incorporate . Due large time requirement searching recording parameters database welcome others add parameters either making pull request package adding information contributing spreadsheet. incorporated database package maintainers. See Data Collation Synthesis Protocol vignette information contributing library epidemiological parameters.","code":"# wrap <epidist> in list to append to database new_db <- append(epi_dist_db, list(covid_incubation))"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"distribution-functions","dir":"Articles","previous_headings":"","what":"Distribution functions","title":"Getting Started with {epiparameter}","text":"<epidist> objects store distributions, mathematical functions distribution can easily extracted directly . often useful access probability density function, cumulative distribution function, quantiles distribution, generate random numbers distribution <epidist> object. distribution functions {epiparameter} allow users easily use .","code":"ebola_incubation <- epidist_db(   disease = \"Ebola\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using WHO Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Blake I, #> Brennan R, Cori A, Donnelly C, Dorigatti I, Dye C, Eckmanns T, Ferguson #> N, Formenty P, Fraser C, Garcia E, Garske T, Hinsley W, Holmes D, #> Hugonnet S, Iyengar S, Jombart T, Krishnan R, Meijers S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). \"West African Ebola #> Epidemic after One Year — Slowing but Not Yet under Control.\" _The New #> England Journal of Medicine_. doi:10.1056/NEJMc1414992 #> <https://doi.org/10.1056/NEJMc1414992>..  #> To retrieve the citation use the 'get_citation' function density(ebola_incubation, at = 0.5) #> [1] 0.03608013 cdf(ebola_incubation, q = 0.5) #> [1] 0.01178094 quantile(ebola_incubation, p = 0.5) #> [1] 8.224347 generate(ebola_incubation, times = 10) #>  [1]  0.7464232  1.8696650  6.9982148 13.0108742  2.1266018  5.4595597 #>  [7]  0.4965333  3.7836991  2.4298127  0.3236717"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"plotting-epidemiological-distributions","dir":"Articles","previous_headings":"","what":"Plotting epidemiological distributions","title":"Getting Started with {epiparameter}","text":"<epidist> objects can easily plotted see PDF CDF distribution.  default plotting range time since infection zero 99th quantile distribution. can altered specifying xlim argument plotting <epidist> object.  plotting function can useful visually comparing epidemiological distributions different publications disease. addition, plotting distribution manually creating <epidist> help check parameters sensible produce expected distribution.","code":"plot(ebola_incubation) plot(ebola_incubation, xlim = c(1, 25))"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"conversion","dir":"Articles","previous_headings":"Parameter conversion and extraction","what":"Conversion","title":"Getting Started with {epiparameter}","text":"Parameters often reported literature mean standard deviation (variance). summary statistics can often (analytically) converted parameters distribution using conversion function package (convert_summary_stats_to_params()). also provide conversion functions opposite direction, parameters summary statistics (convert_params_to_summary_stats()).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"extraction","dir":"Articles","previous_headings":"Parameter conversion and extraction","what":"Extraction","title":"Getting Started with {epiparameter}","text":"functions extract_param() handles extraction parameter estimates summary statistics. two extractions currently supported {epiparameter} percentiles median range.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-percentiles","dir":"Articles","previous_headings":"Extraction Bias","what":"Extraction by percentiles","title":"{epiparameter} Extraction Bias Analysis","text":"First explore extraction percentiles. study reports percentiles distribution, usually symmetrical (e.g. 5th 95th, 2.5th 97.5th). However, instances, asymmetrical percentiles available. test whether asymmetry varying degrees influences bias parameter extraction distributions. set parameter space explore: Now can run extraction point parameter space. set seed control stochasticity estimating parameters, however changing removing seed drastically change results interpretation. extract_param() function re-runs optimisation convergence set tolerance achieved (maximum number iterations reached) reliably return global optimum. theory, help minimise bias instability parameter estimation. See function documentation (?extract_param()) Conversion Extraction vignette details. extraction bias can explored:","code":"distributions <- c(\"gamma\", \"lnorm\", \"weibull\") dist_parameters <- seq(0.5, 2, 0.5) lower_percentiles <- c(2.5, 5, 25, 40) upper_percentiles <- c(60, 95, 97.5)  parameters_perc <- expand.grid(   dist = distributions,   param_1 = dist_parameters,   param_2 = dist_parameters,   lower = lower_percentiles,   upper = upper_percentiles )  # calculate the degree of asymmetry for each percentile combination lw_interval_diff <- abs(0 - parameters_perc$lower) up_interval_diff <- abs(100 - parameters_perc$upper) deg_asym <- abs(lw_interval_diff - up_interval_diff)  # add degree of asymmetry to percentiles parameters_perc <- cbind(parameters_perc, deg_asym)  # divide percentiles by 100 to make them probabilities for quantile functions parameters_perc$lower <- parameters_perc$lower / 100 parameters_perc$upper <- parameters_perc$upper / 100 set.seed(1) estim_params <- vector(\"list\", nrow(parameters_perc)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_perc))) {   dist <- as.character(parameters_perc[params_idx, \"dist\"])   percen <- unname(unlist(parameters_perc[params_idx, c(\"lower\", \"upper\")]))    if (dist == \"lnorm\") {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         meanlog = parameters_perc[params_idx, \"param_1\"],         sdlog = parameters_perc[params_idx, \"param_2\"]       )     )   } else {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         shape = parameters_perc[params_idx, \"param_1\"],         scale = parameters_perc[params_idx, \"param_2\"]       )     )   }    # message about stochastic optimisation suppressed   estim_params[[params_idx]] <- suppressMessages(     extract_param(       type = \"percentiles\",       values = true_values,       distribution = dist,       percentiles = percen     )   ) }  # combine results results <- cbind(parameters_perc, do.call(rbind, estim_params))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"lower\", \"upper\",   \"deg_asym\", \"estim_param_1\", \"estim_param_2\" )  # calculate absolute difference between true parameter and estimated value results <- cbind(   results,   diff_param_1 = abs(results$param_1 - results$estim_param_1),   diff_param_2 = abs(results$param_2 - results$estim_param_2) ) # plot differences by distribution ggplot(data = results) +   geom_point(mapping = aes(     x = diff_param_1,     y = diff_param_2,     colour = deg_asym   )) +   scale_x_continuous(name = \"Parameter 1 Difference (|true - estimated|)\") +   scale_y_continuous(name = \"Parameter 2 Difference (|true - estimated|)\") +   labs(colour = \"Percentile Asym.\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   ) #> Warning in vp$just: partial match of 'just' to 'justification'"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-median-and-range","dir":"Articles","previous_headings":"Extraction Bias","what":"Extraction by median and range","title":"{epiparameter} Extraction Bias Analysis","text":"analysis can repeated, time using summary statistic possibly reported studies: median range data. extraction number samples used infer distribution required can impact possible range exhibited data. Set parameter space: Plot results:","code":"n_samples <- c(10, 50, 100) parameters_range <- expand.grid(   dist = distributions, # same as above   param_1 = dist_parameters, # same as above   param_2 = dist_parameters, # same as above   n_samples = n_samples ) estim_params <- vector(\"list\", nrow(parameters_range)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_range))) {   dist <- as.character(parameters_range[params_idx, \"dist\"])   n_samples <- parameters_range[params_idx, \"n_samples\"]   # while loop to ensure values are min < median < max   resample_values <- TRUE   while (resample_values) {     if (dist == \"lnorm\") {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     } else {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     }     true_values <- c(true_median, true_range)     if (true_values[2] < true_values[1] && true_values[1] < true_values[3]) {       resample_values <- FALSE     }   }   # message about stochastic optimisation suppressed   estim_params[[params_idx]] <- suppressMessages(     expr = extract_param(       type = \"range\",       values = true_values,       distribution = dist,       samples = n_samples     )   ) } #> Warning: Maximum optimisation iterations reached, returning result early.  #> Result may not be reliable.  # combine results results <- cbind(parameters_range, do.call(rbind, estim_params))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"n_samples\", \"estim_param_1\", \"estim_param_2\" )  # calculate absolute difference between true parameter and estimated value results <- cbind(   results,   diff_param_1 = abs(results$param_1 - results$estim_param_1),   diff_param_2 = abs(results$param_2 - results$estim_param_2) ) # plot differences by distribution ggplot(data = results) +   geom_point(     mapping = aes(       x = diff_param_1,       y = diff_param_2,       colour = n_samples     )   ) +   scale_x_continuous(name = \"Parameter 1 Difference (|true - estimated|)\") +   scale_y_continuous(name = \"Parameter 2 Difference (|true - estimated|)\") +   labs(colour = \"No. Samples\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   ) #> Warning in vp$just: partial match of 'just' to 'justification'"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-percentiles-1","dir":"Articles","previous_headings":"Extraction precision","what":"Extraction by percentiles","title":"{epiparameter} Extraction Bias Analysis","text":"two analyses used single extraction (replicate), however, may estimation parameters unstable given set percentiles median range. Therefore, finish test whether repeated extraction parameters single percentile large variance indicate parameter extraction unstable, imprecise, potentially untrustworthy. use parameter space percentiles defined (parameters_perc). Now can run extraction set replicates compute variance parameter estimates replicates.","code":"estim_param_var <- vector(\"list\", nrow(parameters_perc)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_perc))) {   dist <- as.character(parameters_perc[params_idx, \"dist\"])   percen <- unname(unlist(parameters_perc[params_idx, c(\"lower\", \"upper\")]))    if (dist == \"lnorm\") {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         meanlog = parameters_perc[params_idx, \"param_1\"],         sdlog = parameters_perc[params_idx, \"param_2\"]       )     )   } else {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         shape = parameters_perc[params_idx, \"param_1\"],         scale = parameters_perc[params_idx, \"param_2\"]       )     )   }    # message about stochastic optimisation suppressed   estim <- suppressMessages(     replicate(       n = 5,       expr = extract_param(         type = \"percentiles\",         values = true_values,         distribution = dist,         percentiles = percen       )     )   )   estim_param_var[[params_idx]] <- apply(estim, MARGIN = 1, FUN = var) }  # combine results results <- cbind(parameters_perc, do.call(rbind, estim_param_var))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"lower\", \"upper\",   \"deg_asym\", \"estim_param_1_var\", \"estim_param_2_var\" ) ggplot(data = results) +   geom_point(mapping = aes(     x = estim_param_1_var,     y = estim_param_2_var,     colour = deg_asym   )) +   scale_x_continuous(name = \"Parameter 1 Variance\") +   scale_y_continuous(name = \"Parameter 2 Variance\") +   labs(colour = \"Percentile Asym.\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   ) #> Warning in vp$just: partial match of 'just' to 'justification'"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-median-and-range-1","dir":"Articles","previous_headings":"Extraction precision","what":"Extraction by median and range","title":"{epiparameter} Extraction Bias Analysis","text":"test estimation precision can performed extraction median range. plots vignette, bias low precision high extracting parameters gamma, lognormal Weibull distributions percentiles distribution median range data set. asymmetry percentiles sample size data noticeably influence bias parameter extraction. However, ensure reliable extract use cases extract_param() function recommend checking output spurious results.","code":"estim_param_var <- vector(\"list\", nrow(parameters_range)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_range))) {   dist <- as.character(parameters_range[params_idx, \"dist\"])   n_samples <- parameters_range[params_idx, \"n_samples\"]    # while loop to ensure values are min < median < max   resample_values <- TRUE   while (resample_values) {     if (dist == \"lnorm\") {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     } else {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     }     true_values <- c(true_median, true_range)     if (true_values[2] < true_values[1] && true_values[1] < true_values[3]) {       resample_values <- FALSE     }   }   # message about stochastic optimisation suppressed   estim <- suppressMessages(     replicate(       n = 5,       expr = extract_param(         type = \"range\",         values = true_values,         distribution = dist,         samples = n_samples       )     )   )   estim_param_var[[params_idx]] <- apply(estim, MARGIN = 1, FUN = var) } #> Warning: Maximum optimisation iterations reached, returning result early.  #> Result may not be reliable.  # combine results results <- cbind(parameters_range, do.call(rbind, estim_param_var))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"n_samples\", \"estim_param_1_var\",   \"estim_param_2_var\" ) ggplot(data = results) +   geom_point(mapping = aes(     x = estim_param_1_var,     y = estim_param_2_var,     colour = n_samples   )) +   scale_x_continuous(name = \"Parameter 1 Variance\") +   scale_y_continuous(name = \"Parameter 2 Variance\") +   labs(colour = \"No. Samples\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   ) #> Warning in vp$just: partial match of 'just' to 'justification'"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"conversion-versus-extraction","dir":"Articles","previous_headings":"","what":"Conversion versus extraction","title":"Parameter extraction and conversion in {epiparameter}","text":"Use conversion possible extraction avoid possible limitations associated numerical optimisation used extraction function extract_param().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"conversions","dir":"Articles","previous_headings":"","what":"Conversions","title":"Parameter extraction and conversion in {epiparameter}","text":"two conversion functions {epiparameter}: convert_params_to_summary_stats() convert_summary_stats_to_params(). convert_params_to_summary_stats() converts one set statistical distribution parameters common summary statistics, convert_summary_stats_to_params() converts summary statistics set parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"conversion-functions","dir":"Articles","previous_headings":"Conversions","what":"Conversion functions","title":"Parameter extraction and conversion in {epiparameter}","text":"conversion functions generic functions. means different types data can supplied first argument correct operation (method) executed. Currently {epiparameter} provides conversion methods character <epidist>. unclear, see examples conversion functions can work supply either character string <epidist>. conversion functions two arguments. first (x) defines distribution want use second (...) lets put many named parameters summary statistics required. arguments passed ... matched name, therefore need match exactly names expected. See function documentation (?convert_params_to_summary_stats ?convert_summary_stats_to_params names). case <epidist> object supplied, parameters summary statistics required conversion nothing needs given extra arguments (.e. ...). currently supported summary statistic conversions {epiparameter} given distribution.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"using-a-character-string-to-name-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Using a character string to name distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"gamma\", shape = 2.5, scale = 1.5) #> $mean #> [1] 3.75 #>  #> $median #> [1] 1.450487 #>  #> $mode #> [1] 2.25 #>  #> $var #> [1] 5.625 #>  #> $sd #> [1] 2.371708 #>  #> $cv #> [1] 0.6324555 #>  #> $skewness #> [1] 1.264911 #>  #> $ex_kurtosis #> [1] 2.4 convert_summary_stats_to_params(\"gamma\", mean = 2, sd = 2) #> $shape #> [1] 1 #>  #> $scale #> [1] 2 convert_summary_stats_to_params(\"gamma\", mean = 2, var = 2) #> $shape #> [1] 2 #>  #> $scale #> [1] 1 convert_summary_stats_to_params(\"gamma\", mean = 2, cv = 2) #> $shape #> [1] 0.25 #>  #> $scale #> [1] 8"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"using-an-epidist","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Using an <epidist>","title":"Parameter extraction and conversion in {epiparameter}","text":"example parameters provided <epidist> example <epidist> missing parameters supplied ... example summary statistics provided <epidist> example <epidist> missing summary statistics supplied ... usage <epidist> repeated every distribution conversion available {epiparameter}. conversions shown distribution also available using <epidist> object, either parameters summary statistics stored <epidist> supplied via named arguments.","code":"edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 2.5, scale = 1.5) ) #> Citation cannot be created as author, year, journal or title is missing convert_params_to_summary_stats(edist) #> $mean #> [1] 3.75 #>  #> $median #> [1] 1.450487 #>  #> $mode #> [1] 2.25 #>  #> $var #> [1] 5.625 #>  #> $sd #> [1] 2.371708 #>  #> $cv #> [1] 0.6324555 #>  #> $skewness #> [1] 1.264911 #>  #> $ex_kurtosis #> [1] 2.4 edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\" ) #> Citation cannot be created as author, year, journal or title is missing #> No adequate summary statistics available to calculate the parameters of the gamma distribution #> Unparameterised <epidist> object convert_params_to_summary_stats(edist, shape = 2.5, scale = 1.5) #> $mean #> [1] 3.75 #>  #> $median #> [1] 1.450487 #>  #> $mode #> [1] 2.25 #>  #> $var #> [1] 5.625 #>  #> $sd #> [1] 2.371708 #>  #> $cv #> [1] 0.6324555 #>  #> $skewness #> [1] 1.264911 #>  #> $ex_kurtosis #> [1] 2.4 edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\",   summary_stats = create_epidist_summary_stats(mean = 3.75, sd = 2.37) ) #> Citation cannot be created as author, year, journal or title is missing convert_summary_stats_to_params(edist) #> $shape #> [1] 2.503605 #>  #> $scale #> [1] 1.49784 edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\" ) #> Citation cannot be created as author, year, journal or title is missing #> No adequate summary statistics available to calculate the parameters of the gamma distribution #> Unparameterised <epidist> object convert_summary_stats_to_params(edist, mean = 3.75, sd = 2.37) #> $shape #> [1] 2.503605 #>  #> $scale #> [1] 1.49784"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"lognormal-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Lognormal distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"lnorm\", meanlog = 2.5, sdlog = 1.5) #> $mean #> [1] 37.52472 #>  #> $median #> [1] 12.18249 #>  #> $mode #> [1] 1.284025 #>  #> $var #> [1] 11951.62 #>  #> $sd #> [1] 109.3235 #>  #> $cv #> [1] 2.913372 #>  #> $skewness #> [1] 33.46805 #>  #> $ex_kurtosis #> [1] 10075.25 convert_summary_stats_to_params(\"lnorm\", mean = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #>  #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(\"lnorm\", mean = 2, var = 2) #> $meanlog #> [1] 0.4904146 #>  #> $sdlog #> [1] 0.6367614 convert_summary_stats_to_params(\"lnorm\", mean = 2, cv = 2) #> $meanlog #> [1] -0.1115718 #>  #> $sdlog #> [1] 1.268636 convert_summary_stats_to_params(\"lnorm\", median = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #>  #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(\"lnorm\", median = 2, var = 2) #> $meanlog #> [1] 0.4904146 #>  #> $sdlog #> [1] 0.6367614"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"weibull-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Weibull distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"weibull\", shape = 2.5, scale = 1.5) #> $mean #> [1] 1.330896 #>  #> $median #> [1] 1.295452 #>  #> $mode #> [1] 1.22279 #>  #> $var #> [1] 0.3243301 #>  #> $sd #> [1] 0.5694998 #>  #> $cv #> [1] 0.4279072 #>  #> $skewness #> [1] 0.3586318 #>  #> $ex_kurtosis #> [1] -0.1432169 convert_summary_stats_to_params(\"weibull\", mean = 2, sd = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 1.000016 #>  #> $scale #> [1] 2.000014 convert_summary_stats_to_params(\"weibull\", mean = 2, var = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 1.435521 #>  #> $scale #> [1] 2.202641 convert_summary_stats_to_params(\"weibull\", mean = 2, cv = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 0.5427068 #>  #> $scale #> [1] 1.150547"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"negative-binomial-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Negative binomial distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"nbinom\", prob = 0.5, dispersion = 0.5) #> $mean #> [1] 0.5 #>  #> $median #> [1] 0 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 1 #>  #> $sd #> [1] 1 #>  #> $cv #> [1] 2 #>  #> $skewness #> [1] 3 #>  #> $ex_kurtosis #> [1] 12.25 convert_summary_stats_to_params(\"nbinom\", mean = 1, sd = 1) #> $prob #> [1] 1 #>  #> $dispersion #> [1] Inf convert_summary_stats_to_params(\"nbinom\", mean = 1, var = 1) #> $prob #> [1] 1 #>  #> $dispersion #> [1] Inf convert_summary_stats_to_params(\"nbinom\", mean = 1, cv = 1) #> $prob #> [1] 1 #>  #> $dispersion #> [1] Inf"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"geometric-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Geometric distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"geom\", prob = 0.5) #> $mean #> [1] 1 #>  #> $median #> [1] 0 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 2 #>  #> $sd #> [1] 1.414214 #>  #> $cv #> [1] 1.414214 #>  #> $skewness #> [1] 2.12132 #>  #> $ex_kurtosis #> [1] 6.5 convert_summary_stats_to_params(\"geom\", mean = 1) #> $prob #> [1] 0.5"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"extraction","dir":"Articles","previous_headings":"","what":"Extraction","title":"Parameter extraction and conversion in {epiparameter}","text":"two methods extraction implemented {epiparameter}. One estimate parameters given values two percentiles, estimate parameters given median range data. extractions implemented extract_param() function. demonstrate extraction using percentiles. type \"percentiles\", values values reported percentiles, given vector. percentiles, given 0 1, specified vector percentiles. example uses values 1 10 2.5th 97.5th percentile, respectively. example estimate parameters gamma distribution, extraction also implemented lognormal, normal Weibull distributions, specifying \"lnorm\", \"norm\" \"weibull\". message shown running extract_param() make user aware estimates completely reliable due use numerical optimisation. Rerunning function finding parameters returned indicates successfully converged. issue mostly overcome internal setup extract_param() function searches convergence consistent parameter estimates returning user. alternative extraction, median range, can achieved specifying type = \"range\" using samples argument instead percentiles argument. using type = \"percentiles\" samples argument ignored using type = \"range\" percentiles argument ignored. section mentioned extract_param() internal mechanism check parameters consistently converged estimates several optimisation iterations. tolerance convergence number times optimisation can repeated specified control argument extract_param(). set default (tolerance = 1e-5 max_iter = 1000), thus need specified user (shown examples). case maximum number optimisation iterations reached, calculation terminates returning recent optimisation result user along warning message. reasoning default maximum number iterations limit computation time prevent function cycling optimisation routines without converging consistent answer. runtime important parameter accuracy paramount maximum number iterations can increased tolerance decreased. control settings work identically extracting percentiles median range. Donnelly et al. (2003) provides mean variance gamma distribution incubation period SARS. conversion can achieved using general conversion function (convert_summary_stats_to_params()).","code":"extract_param(   type = \"percentiles\",   values = c(1, 10),   distribution = \"gamma\",   percentiles = c(0.025, 0.975) ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>    shape    scale  #> 3.358210 1.284184 extract_param(   type = \"range\",   values = c(10, 5, 15),   distribution = \"lnorm\",   samples = 25 ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>  meanlog    sdlog  #> 2.302584 3.939920 # set seed to ensure warning is produced set.seed(1)  # lower maximum iteration to show warning extract_param(   type = \"range\",   values = c(10, 1, 25),   distribution = \"lnorm\",   samples = 100,   control = list(max_iter = 100) ) #> Warning: Maximum optimisation iterations reached, returning result early.  #> Result may not be reliable. #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>   meanlog     sdlog  #> 2.3025851 0.7942061 # SARS gamma mean and var to shape and scale convert_summary_stats_to_params(\"gamma\", mean = 6.37, var = 16.7) #> $shape #> [1] 2.429754 #>  #> $scale #> [1] 2.621664"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"use-cases","dir":"Articles","previous_headings":"Extraction","what":"Use cases","title":"Parameter extraction and conversion in {epiparameter}","text":"present examples published epidemiological parameters distributions functions outlined can applied get parameters distribution. 75th percentiles reported lognormal distribution Nolen et al. (2016) incubation period mpox (monkeypox). median range provided Thornhill et al. (2022) mpox, want calculate parameters lognormal distribution.","code":"# Mpox lnorm from 75th percentiles in WHO data extract_param(   type = \"percentiles\",   values = c(6, 13),   distribution = \"lnorm\",   percentiles = c(0.125, 0.875) ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>   meanlog     sdlog  #> 2.1783544 0.3360684 # Mpox lnorm from median and range in 2022: extract_param(   type = \"range\",   values = c(7, 3, 20),   distribution = \"lnorm\",   samples = 23 ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>  meanlog    sdlog  #> 1.945910 4.735285"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"assuming-distributions","dir":"Articles","previous_headings":"Extraction","what":"Assuming distributions","title":"Parameter extraction and conversion in {epiparameter}","text":"can case study report summary statistics unspecified distribution just raw data. cases parameterised distribution required downstream analysis functional, parametric, form may assumed. distribution delay distribution (.e. serial interval incubation period) can often sensible assume right-skewed distribution : gamma, lognormal Weibull distributions. also commonly fit distributions epidemiological analysis delay distributions. However, one take care assuming distribution may drastically influence interpretation application epidemiological parameters.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Joshua W. Lambert. Author, maintainer, copyright holder. Adam Kucharski. Author, copyright holder. Carmen Tamayo. Author. Hugo Gruson. Contributor, reviewer. Sebastian Funk. Contributor. Pratik Gupte. Reviewer.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Lambert J, Kucharski , Tamayo C (2024). epiparameter: Library Epidemiological Parameters Helper Functions Classes. doi:10.5281/zenodo.11110881, https://github.com/epiverse-trace/epiparameter/,https://epiverse-trace.github.io/epiparameter/.","code":"@Manual{,   title = {epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes},   author = {Joshua W. Lambert and Adam Kucharski and Carmen Tamayo},   year = {2024},   doi = {10.5281/zenodo.11110881},   url = {https://github.com/epiverse-trace/epiparameter/, https://epiverse-trace.github.io/epiparameter/}, }"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"epiparameter-","dir":"","previous_headings":"","what":"Library of Epidemiological Parameters with Helper Functions and Classes","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"epiparameter R package contains library epidemiological parameters infectious diseases set classes helper functions able work data. also includes functions extract convert parameters reported summary statistics. epiparameter developed Centre Mathematical Modelling Infectious Diseases London School Hygiene Tropical Medicine part Epiverse-TRACE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"easiest way install development version epiparameter use pak package:","code":"# check whether {pak} is installed if(!require(\"pak\")) install.packages(\"pak\") pak::pak(\"epiverse-trace/epiparameter\")"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"quick-start","dir":"","previous_headings":"","what":"Quick start","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"load library epidemiological parameters R: results list database entries. entry library <epidist> object. results can filtered disease epidemiological distribution. set single_epidist = TRUE want single database entry returned, default (single_epidist = FALSE) return database entries match disease (disease) epidemiological distribution (epi_dist). quickly view list epidemiological distributions returned epidist_db() table, parameter_tbl() gives summary data, offers ability subset data disease, pathogen epidemiological distribution (epi_dist). <epidist> object can plotted.  CDF can also plotted setting cumulative = TRUE.","code":"library(epiparameter) epidists <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function epidists #> List of <epidist> objects #>   Number of entries in library: 122 #>   Number of studies in library: 47 #>   Number of diseases: 23 #>   Number of delay distributions: 112 #>   Number of offspring distributions: 10 influenza_incubation <- epidist_db(   disease = \"influenza\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using Virlogeux V, Li M, Tsang T, Feng L, Fang V, Jiang H, Wu P, Zheng J, Lau #> E, Cao Y, Qin Y, Liao Q, Yu H, Cowling B (2015). \"Estimating the #> Distribution of the Incubation Periods of Human Avian Influenza A(H7N9) #> Virus Infections.\" _American Journal of Epidemiology_. #> doi:10.1093/aje/kwv115 <https://doi.org/10.1093/aje/kwv115>..  #> To retrieve the citation use the 'get_citation' function influenza_incubation #> Disease: Influenza #> Pathogen: Influenza-A-H7N9 #> Epi Distribution: incubation period #> Study: Virlogeux V, Li M, Tsang T, Feng L, Fang V, Jiang H, Wu P, Zheng J, Lau #> E, Cao Y, Qin Y, Liao Q, Yu H, Cowling B (2015). \"Estimating the #> Distribution of the Incubation Periods of Human Avian Influenza A(H7N9) #> Virus Infections.\" _American Journal of Epidemiology_. #> doi:10.1093/aje/kwv115 <https://doi.org/10.1093/aje/kwv115>. #> Distribution: weibull #> Parameters: #>   shape: 2.101 #>   scale: 3.839 parameter_tbl(epidists) #> # Parameter table: #> # A data frame:    122 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 Adenovi… Adenovi… incubation peri… lnorm             Lessl…  2009          14 #>  2 Human C… Human_C… incubation peri… lnorm             Lessl…  2009          13 #>  3 SARS     SARS-Co… incubation peri… lnorm             Lessl…  2009         157 #>  4 Influen… Influen… incubation peri… lnorm             Lessl…  2009         151 #>  5 Influen… Influen… incubation peri… lnorm             Lessl…  2009          90 #>  6 Influen… Influen… incubation peri… lnorm             Lessl…  2009          78 #>  7 Measles  Measles… incubation peri… lnorm             Lessl…  2009          55 #>  8 Parainf… Parainf… incubation peri… lnorm             Lessl…  2009          11 #>  9 RSV      RSV      incubation peri… lnorm             Lessl…  2009          24 #> 10 Rhinovi… Rhinovi… incubation peri… lnorm             Lessl…  2009          28 #> # ℹ 112 more rows parameter_tbl(   epidists,   epi_dist = \"onset to hospitalisation\" ) #> # Parameter table: #> # A data frame:    5 × 7 #>   disease  pathogen  epi_distribution prob_distribution author  year sample_size #>   <chr>    <chr>     <chr>            <chr>             <chr>  <dbl>       <dbl> #> 1 MERS     MERS-Cov  onset to hospit… <NA>              Assir…  2013          23 #> 2 COVID-19 SARS-CoV… onset to hospit… gamma             Linto…  2020         155 #> 3 COVID-19 SARS-CoV… onset to hospit… gamma             Linto…  2020          34 #> 4 COVID-19 SARS-CoV… onset to hospit… lnorm             Linto…  2020         155 #> 5 COVID-19 SARS-CoV… onset to hospit… lnorm             Linto…  2020          34 plot(influenza_incubation) plot(influenza_incubation, cumulative = TRUE)"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"parameter-conversion-and-extraction","dir":"","previous_headings":"Quick start","what":"Parameter conversion and extraction","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"parameters distribution can converted mean standard deviation. epiparameter implement variety distributions: gamma lognormal Weibull negative binomial geometric parameters probability distribution can also extracted summary statistics, example, percentiles distribution, median range data. can done : gamma lognormal Weibull normal","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"contributing-to-library-of-epidemiological-parameters","dir":"","previous_headings":"","what":"Contributing to library of epidemiological parameters","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"like contribute different epidemiological parameters stored epiparameter package, can add data public google sheet. spreadsheet contains two example entries guide fields can accept. monitoring sheet new entries subsequently included package. Alternatively, parameters can added JSON file holding data base directly via Pull Request. can find explanation accepted entries column data dictionary.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"help","dir":"","previous_headings":"","what":"Help","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"report bug please open issue","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"contribute","dir":"","previous_headings":"","what":"Contribute","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"Contributions epiparameter welcomed. package contributing guide.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"Please note epiparameter project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"citing-this-package","dir":"","previous_headings":"","what":"Citing this package","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"","code":"citation(\"epiparameter\") #> To cite package 'epiparameter' in publications use: #>  #>   Lambert J, Kucharski A, Tamayo C (2024). _epiparameter: Library of #>   Epidemiological Parameters with Helper Functions and Classes_. #>   doi:10.5281/zenodo.11110881 #>   <https://doi.org/10.5281/zenodo.11110881>, #>   <https://github.com/epiverse-trace/epiparameter/,https://epiverse-trace.github.io/epiparameter/>. #>  #> A BibTeX entry for LaTeX users is #>  #>   @Manual{, #>     title = {epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes}, #>     author = {Joshua W. Lambert and Adam Kucharski and Carmen Tamayo}, #>     year = {2024}, #>     doi = {10.5281/zenodo.11110881}, #>     url = {https://github.com/epiverse-trace/epiparameter/, #> https://epiverse-trace.github.io/epiparameter/}, #>   }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.data.frame() method for <epidist> class — as.data.frame.epidist","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":".data.frame() method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"","code":"# S3 method for epidist as.data.frame(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"<data.frame> single row.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"<data.frame> returned contain atomic columns (.e. one object per row), columns lists (.e. multiple objects per row). list columns can contain lists S3 objects (e.g. <bibentry> object citation column).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":".data.frame() method <multi_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"","code":"# S3 method for multi_epidist as.data.frame(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"x <multi_epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"<data.frame> many rows length input list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"<data.frame> returned contain atomic columns (.e. one object per row), columns lists (.e. multiple objects per row). list columns can contain lists S3 objects (e.g. <bibentry> object citation column).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.function() method for <epidist> class — as.function.epidist","title":"as.function() method for <epidist> class — as.function.epidist","text":"Converts <epidist> object distribution function (see epidist_distribution_functions), either probability density/mass function, (density), cumulative distribution function (cdf), random number generator (generate), quantile (quantile).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"as.function() method for <epidist> class — as.function.epidist","text":"","code":"# S3 method for epidist as.function(x, func_type = c(\"density\", \"cdf\", \"generate\", \"quantile\"), ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"as.function() method for <epidist> class — as.function.epidist","text":"x <epidist> object. func_type single character string specifying distribution convert <epidist> object . Default \"density\". options \"cdf\", \"generate\", \"quantile\". ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"as.function() method for <epidist> class — as.function.epidist","text":"function object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"as.function() method for <epidist> class — as.function.epidist","text":"function returned takes single required argument x.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"Convert tabular information <data.frame> <epidist>. information <data.frame> converted <epidist> function error.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"","code":"# S3 method for data.frame as_epidist(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"x <data.frame>. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"<epidist> object list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"","code":"# stub"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert to an <epidist> object — as_epidist","title":"Convert to an <epidist> object — as_epidist","text":"Convert R object <epidist> object. conversion possible function error.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert to an <epidist> object — as_epidist","text":"","code":"as_epidist(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert to an <epidist> object — as_epidist","text":"x object used select method. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert to an <epidist> object — as_epidist","text":"<epidist> object list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert to an <epidist> object — as_epidist","text":"create full citation information article table epireview package corresponding entry need passed function via ... argument. argument called article, matched name $. specify probability distribution pass character string function via ... argument. argument called prob_dist. example, specify gamma distribution: as_epidist(x, prob_dist = \"gamma\"). Warning: distributions specified via prob_dist argument overwrite probability distribution specified x argument. example, probability distribution given epireview entry prob_dist argument specified function may error return unparameterised <epidist> parameterisation becomes incompatible. Valid probability distributions : \"gamma\", \"lnorm\", \"weibull\", \"nbinom\", \"geom\", \"pois\", \"norm\", \"exp\".","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"function can used cases data fitted distribution openly available summary statistics distribution reported data scraped plot quantiles needed order use extract_param() function.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"","code":"calc_disc_dist_quantile(prob, days, quantile)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"prob numeric vector probabilities. days numeric vector days. quantile single numeric vector numerics specifying quantiles extract distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"named vector quantiles.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"","code":"prob <- dgamma(seq(0, 10, length.out = 21), shape = 2, scale = 2) days <- seq(0, 10, 0.5) quantiles <- c(0.025, 0.975) calc_disc_dist_quantile(prob = prob, days = days, quantile = quantiles) #> 0.025 0.975  #>     0     9"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"parameters probability distribution provided (e.g. describing distribution literature) instead summary statistics distribution provided, parameters can usually calculated summary statistics. function can provide convenient wrapper around convert_summary_stats_to_params() extract_param() known summary statistics can used calculate parameters distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"","code":"calc_dist_params(prob_dist, prob_dist_params, summary_stats, sample_size)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters. summary_stats list summary statistics, use create_epidist_summary_stats() create list. list can include summary statistics inferred distribution mean standard deviation, quantiles distribution, information data used fit distribution lower upper range. summary statistics can also include uncertainty around metrics confidence interval around mean standard deviation. sample_size sample size data. needed falling back using median-range extraction calculation.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"hierarchy methods : Conversion prioritised mean standard deviation available mostly analytical conversions (except one Weibull conversions). Next method possible extraction percentiles. method requires lower percentile ((0-50]) upper percentile ((50-100)). multiple percentiles ranges provided lowest value used calculation. last method extraction using median range data.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"function try prevent optimisation local optimum thus checks whether multiple optimisation routines consistently finding parameter values within set tolerance.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"","code":"check_optim_conv(optim_params_list, optim_params, tolerance)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"optim_params_list list, element output stats::optim(). See ?optim details. optim_params list given output stats::optim(). tolerance numeric specifying within disparity convergence parameter estimates function minimisation accepted.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"Boolean","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"Convert parameters range distributions number summary statistics. summary statistics calculated analytically given parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"","code":"convert_params_to_summary_stats(x, ...)  # S3 method for character convert_params_to_summary_stats(   x = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"),   ... )  # S3 method for epidist convert_params_to_summary_stats(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"x R object. ... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"distribution names parameter names follow style distributions R, example lognormal distribution lnorm, parameters meanlog sdlog.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"","code":"# example using characters convert_params_to_summary_stats(\"lnorm\", meanlog = 1, sdlog = 2) #> $mean #> [1] 20.08554 #>  #> $median #> [1] 2.718282 #>  #> $mode #> [1] 0.04978707 #>  #> $var #> [1] 21623.04 #>  #> $sd #> [1] 147.0477 #>  #> $cv #> [1] 7.321076 #>  #> $skewness #> [1] 414.3593 #>  #> $ex_kurtosis #> [1] 9220557 #>  convert_params_to_summary_stats(\"gamma\", shape = 1, scale = 1) #> $mean #> [1] 1 #>  #> $median #> [1] 0.6931472 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 1 #>  #> $sd #> [1] 1 #>  #> $cv #> [1] 1 #>  #> $skewness #> [1] 2 #>  #> $ex_kurtosis #> [1] 6 #>  convert_params_to_summary_stats(\"nbinom\", prob = 0.5, dispersion = 2) #> $mean #> [1] 2 #>  #> $median #> [1] 1 #>  #> $mode #> [1] 1 #>  #> $var #> [1] 4 #>  #> $sd #> [1] 2 #>  #> $cv #> [1] 1 #>  #> $skewness #> [1] 1.5 #>  #> $ex_kurtosis #> [1] 4 #>   # example using <epidist> epidist <- epidist_db(single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function convert_params_to_summary_stats(epidist) #> $mean #> [1] 9.7 #>  #> $median #> [1] 2.576957 #>  #> $mode #> [1] 0.1818772 #>  #> $var #> [1] 1239.04 #>  #> $sd #> [1] 35.2 #>  #> $cv #> [1] 3.628866 #>  #> $skewness #> [1] 58.67393 #>  #> $ex_kurtosis #> [1] 46586.04 #>   # example using <epidist> and specifying parameters epidist <- epidist_db(   disease = \"Influenza\",   author = \"Virlogeux\",   subset = prob_dist == \"weibull\" ) #> Returning 4 results that match the criteria (3 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function convert_params_to_summary_stats(epidist[[2]], shape = 1, scale = 1) #> $mean #> [1] 1 #>  #> $median #> [1] 0.6931472 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 1 #>  #> $sd #> [1] 1 #>  #> $cv #> [1] 1 #>  #> $skewness #> [1] 2 #>  #> $ex_kurtosis #> [1] 6 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"Convert summary statistics range distributions distribution's parameters. summary statistics calculated analytically given parameters. exception Weibull distribution uses root finding numerical method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"","code":"convert_summary_stats_to_params(x, ...)  # S3 method for character convert_summary_stats_to_params(   x = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"),   ... )  # S3 method for epidist convert_summary_stats_to_params(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"x R object. ... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"list either one two elements (depending many parameters distribution ).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"Summary statistics named accordingly (case-sensitive): mean: mean median: median mode: mode variance: var standard deviation: sd coefficient variation: cv skewness: skewness excess kurtosis: ex_kurtosis Note: combinations summary statistics can converted distribution parameters. case function error stating parameters calculated given input. distribution names parameter names follow style distributions R, example lognormal distribution lnorm, parameters meanlog sdlog.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"","code":"# examples using characters convert_summary_stats_to_params(\"lnorm\", mean = 1, sd = 1) #> $meanlog #> [1] -0.3465736 #>  #> $sdlog #> [1] 0.8325546 #>  convert_summary_stats_to_params(\"weibull\", mean = 2, var = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 1.435521 #>  #> $scale #> [1] 2.202641 #>  convert_summary_stats_to_params(\"geom\", mean = 2) #> $prob #> [1] 0.3333333 #>   # examples using <epidist> epidist <- epidist_db(single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function convert_summary_stats_to_params(epidist) #> $meanlog #> [1] 0.9466094 #>  #> $sdlog #> [1] 1.628199 #>   # example using <epidist> and specifying summary stats epidist$summary_stats <- list() convert_summary_stats_to_params(epidist, mean = 10, sd = 2) #> $meanlog #> [1] 2.282975 #>  #> $sdlog #> [1] 0.1980422 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a citation for an <epidist> object — create_epidist_citation","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"helper function creating <epidist> object create citation list sensible defaults, type checking arguments help remember citation information accepted list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"","code":"create_epidist_citation(   author = utils::person(),   year = NA_integer_,   title = NA_character_,   journal = NA_character_,   doi = NA_character_,   pmid = NA_integer_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"author Either <person>, character string, vector list characters case multiple authors. Specify full name (\"<given name>\" \"<family name>\"). using characters make sure name can converted <person> (see .person()). Use white space separation names. Multiple names can stored within single <person> (see person()). year numeric year publication. title character string title article published epidemiological parameters. journal character string name journal published article published epidemiological parameters. can also pre-print server, e.g., medRxiv. doi character string Digital Object Identifier (DOI) assigned papers unique paper. pmid character string PubMed unique identifier number (PMID) assigned papers give unique identifier within PubMed.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"<bibentry> object citation","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"function acts wrapper around bibentry() create citations sources reporting epidemiological parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"","code":"create_epidist_citation(   author = person(given = \"John\", family = \"Smith\"),   year = 2002,   title = \"COVID-19 incubation period\",   journal = \"Epi Journal\",   doi = \"10.19832/j.1366-9516.2012.09147.x\" ) #> Using Smith J (2002). “COVID-19 incubation period.” _Epi Journal_. #> doi:10.19832/j.1366-9516.2012.09147.x #> <https://doi.org/10.19832/j.1366-9516.2012.09147.x>.  #> To retrieve the citation use the 'get_citation' function #> Smith J (2002). “COVID-19 incubation period.” _Epi Journal_. #> doi:10.19832/j.1366-9516.2012.09147.x #> <https://doi.org/10.19832/j.1366-9516.2012.09147.x>."},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify metadata associated with data set — create_epidist_metadata","title":"Specify metadata associated with data set — create_epidist_metadata","text":"helper function creating <epidist> object create metadata list sensible defaults, type checking arguments help remember metadata list structure (element names).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify metadata associated with data set — create_epidist_metadata","text":"","code":"create_epidist_metadata(   sample_size = NA_integer_,   region = NA_character_,   transmission_mode = NA_character_,   vector = NA_character_,   extrinsic = FALSE,   inference_method = NA_character_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify metadata associated with data set — create_epidist_metadata","text":"sample_size sample data used fit delay distribution. usually number people data primary possibly secondary event interest. cases sample size stated NA can used. region geographical location data collected. can either given sub-national, national, continental. Multiple nested regions can given comma separated. region specified NA can given. transmission_mode character string specifying pathogen transmitted. information used determine whether epidemiological parameters vector-borne disease (.e. transmitted humans intermediate vector), specified transmission_mode = \"vector_borne\". vector name vector transmitting vector-borne disease. can common name, latin binomial name specific vector species. common name taxonomic name can given one given parentheses. disease vector-borne NA given. extrinsic boolean value defining whether data entry extrinsic delay distribution, extrinsic incubation period. field required intrinsic extrinsic delay distributions stored separate entries database can linked. disease vector-borne FALSE given. See Details explanation extrinsic distribution. inference_method type inference used fit delay distribution data. Abbreviations model fitting techniques can specified long non-ambiguous. field used determine whether uncertainty intervals possibly specified fields : confidence intervals (case maximum likelihood), credible intervals (case bayesian inference). Uncertainty bounds another types inference methods, inference method unstated assumed confidence intervals. inference method unknown disease probability distribution NA can given.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify metadata associated with data set — create_epidist_metadata","text":"named list containing information sample size study, geography, whether disease vector-borne whether intrinsic extrinsic distribution well method distribution parameter estimation.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Specify metadata associated with data set — create_epidist_metadata","text":"vector-borne diseases transmissibility disease dependent time taken host (.e. human) become infectious, also time takes vector become infectious. Therefore, extrinsic delay, vector infected yet infectious can role spread disease.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify metadata associated with data set — create_epidist_metadata","text":"","code":"# it will automatically populate the fields with defaults if left empty create_epidist_metadata() #> $sample_size #> [1] NA #>  #> $region #> [1] NA #>  #> $transmission_mode #> [1] NA #>  #> $vector #> [1] NA #>  #> $extrinsic #> [1] FALSE #>  #> $inference_method #> [1] NA #>   # supplying each field create_epidist_metadata(   sample_size = 10,   region = \"UK\",   transmission_mode = \"vector_borne\",   vector = \"mosquito\",   extrinsic = FALSE,   inference_method = \"MLE\" ) #> $sample_size #> [1] 10 #>  #> $region #> [1] \"UK\" #>  #> $transmission_mode #> [1] \"vector_borne\" #>  #> $vector #> [1] \"mosquito\" #>  #> $extrinsic #> [1] FALSE #>  #> $inference_method #> [1] \"MLE\" #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"helper function creating <epidist> object create method assessment list sensible defaults, type checking arguments help remember method assessments can accepted list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"","code":"create_epidist_method_assess(   censored = NA,   right_truncated = NA,   phase_bias_adjusted = NA )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"censored boolean logical whether study used single double interval censoring methods infer delay distribution right_truncated boolean logical whether study used right- truncation methods infer delay distribution phase_bias_adjusted boolean logical whether study adjusted phase bias methods infer delay distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"named list three elements","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"Currently, method assessment focuses common methodological aspects delay distributions (e.g. incubation period, serial interval, etc.), currently take account methodological aspects may important fitting offspring distributions data disease (super)spreading.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"","code":"create_epidist_method_assess(   censored = FALSE,   right_truncated = FALSE,   phase_bias_adjusted = FALSE ) #> $censored #> [1] FALSE #>  #> $right_truncated #> [1] FALSE #>  #> $phase_bias_adjusted #> [1] FALSE #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a distribution object — create_epidist_prob_dist","title":"Create a distribution object — create_epidist_prob_dist","text":"Creates S3 class holding distribution parameters probability distribution name, parameters distribution truncation discretisation. class holding distribution depends whether discretised distribution. continuous discrete distributions S3 classes distributional package used, discretised continuous distributions S3 class distcrete package used. details properties distribution classes respective package see documentation (either ?distributional ?distcrete)","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a distribution object — create_epidist_prob_dist","text":"","code":"create_epidist_prob_dist(   prob_dist,   prob_dist_params,   discretise = FALSE,   truncation = NA,   ... )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a distribution object — create_epidist_prob_dist","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters. discretise boolean logical whether distribution discretised. Default FALSE assumes continuous probability distribution truncation numeric specifying truncation point inferred distribution truncated, NA unknown. ... dots Extra arguments passed distributional distcrete functions construct S3 distribution objects. see arguments can adjusted discretised distributions see distcrete::distcrete(), distributions see ?distributional documentation find specific distribution constructor function, e.g. Gamma distribution see distributional::dist_gamma().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a distribution object — create_epidist_prob_dist","text":"S3 class containing probability distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a distribution object — create_epidist_prob_dist","text":"Truncation enabled continuous distributions truncation implemented distcrete. default discretisation continuous distributions uses discretisation interval (interval) 1. unit distribution days, discretised day. endpoint weighting (w) discretisation 1. w can [0,1]. information please see distcrete::distcrete().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a distribution object — create_epidist_prob_dist","text":"","code":"# example with continuous distribution without truncation create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = FALSE,   truncation = NA ) #> <distribution[1]> #> [1] Γ(1, 1)  # example with continuous distribution with truncation create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = FALSE,   truncation = 10 ) #> <distribution[1]> #> [1] Γ(1, 1)[-Inf,10]  # example with discrete distribution create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = TRUE,   truncation = NA ) #> A discrete distribution #>   name: gamma #>   parameters: #>     shape: 1 #>     scale: 1  # example passing extra arguments to distcrete create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = TRUE,   truncation = NA,   w = 0.5 ) #> A discrete distribution #>   name: gamma #>   parameters: #>     shape: 1 #>     scale: 1"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify the geography of the data entry — create_epidist_region","title":"Specify the geography of the data entry — create_epidist_region","text":"geography data set can single geographical region either continent, country, region city level. specifying level geography fields may deduced.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify the geography of the data entry — create_epidist_region","text":"","code":"create_epidist_region(   continent = NA_character_,   country = NA_character_,   region = NA_character_,   city = NA_character_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify the geography of the data entry — create_epidist_region","text":"continent character string specifying continent. country character string specifying country. region character string specifying region. city character string specifying city.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify the geography of the data entry — create_epidist_region","text":"named list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify the geography of the data entry — create_epidist_region","text":"","code":"create_epidist_region(country = \"UK\") #> $continent #> [1] NA #>  #> $country #> [1] \"UK\" #>  #> $region #> [1] NA #>  #> $city #> [1] NA #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify reported summary statistics — create_epidist_summary_stats","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"helper function creating <epidist> object create summary statistics list sensible defaults, type checking arguments help remember summary statistics can accepted list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"","code":"create_epidist_summary_stats(   mean = NA_real_,   mean_ci_limits = c(NA_real_, NA_real_),   mean_ci = NA_real_,   sd = NA_real_,   sd_ci_limits = c(NA_real_, NA_real_),   sd_ci = NA_real_,   median = NA_real_,   median_ci_limits = c(NA_real_, NA_real_),   median_ci = NA_real_,   lower_range = NA_real_,   upper_range = NA_real_,   quantiles = NA_real_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"mean numeric mean (expectation) probability distribution. mean_ci_limits numeric vector length two confidence interval around mean. mean_ci numeric specifying confidence interval width, e.g. 95 95% CI sd numeric standard deviation probability distribution. sd_ci_limits numeric vector length 2 confidence interval around standard deviation. sd_ci numeric specifying confidence interval width, e.g. 95 95% confidence interval. median numeric median probability distribution. median_ci_limits numeric vector length two confidence interval around median. median_ci numeric specifying confidence interval width median. lower_range lower range data, used infer parameters distribution provided. upper_range upper range data, used infer parameters distribution provided. quantiles numeric vector quantiles distribution. quantiles provided default empty vector 2.5th, 5th, 25th, 75th, 95th, 97.5th quantiles supplied.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"nested list summary statistics. highest level $centre_spread $quantiles $range $dispersion","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"","code":"# mean and standard deviation create_epidist_summary_stats(mean = 5, sd = 2) #> $mean #> [1] 5 #>  #> $mean_ci_limits #> [1] NA NA #>  #> $mean_ci #> [1] NA #>  #> $sd #> [1] 2 #>  #> $sd_ci_limits #> [1] NA NA #>  #> $sd_ci #> [1] NA #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] NA NA #>   # mean and standard deviation with uncertainty create_epidist_summary_stats(   mean = 4,   mean_ci_limits = c(2.1, 5.7),   mean_ci = 95,   sd = 0.7,   sd_ci_limits = c(0.3, 1.1),   sd_ci = 95 ) #> $mean #> [1] 4 #>  #> $mean_ci_limits #> [1] 2.1 5.7 #>  #> $mean_ci #> [1] 95 #>  #> $sd #> [1] 0.7 #>  #> $sd_ci_limits #> [1] 0.3 1.1 #>  #> $sd_ci #> [1] 95 #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] NA NA #>   # median and range create_epidist_summary_stats(   median = 5,   lower_range = 1,   upper_range = 13 ) #> $mean #> [1] NA #>  #> $mean_ci_limits #> [1] NA NA #>  #> $mean_ci #> [1] NA #>  #> $sd #> [1] NA #>  #> $sd_ci_limits #> [1] NA NA #>  #> $sd_ci #> [1] NA #>  #> $median #> [1] 5 #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1]  1 13 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify distribution parameter uncertainty — create_epidist_uncertainty","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"helper function creating uncertainty parameters distribution <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"","code":"create_epidist_uncertainty(ci_limits = NA_real_, ci, ci_type)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"ci_limits numeric vector length two lower upper bound confidence interval credible interval. ci numeric specifying interval ci, e.g. 95 95% ci. ci_type character string, either \"confidence interval\" \"credible interval\".","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"List three elements: $ci_limits upper lower bounds CI (either confidence interval credible interval) (.e. two element numeric vector). $ci interval (e.g. 95 95% CI) given single numeric. $ci_type character string specifying type uncertainty (can either \"confidence interval\" \"credible interval\").","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"","code":"# example with uncertainty for a single parameter create_epidist_uncertainty(   ci_limits = c(1, 3),   ci = 95,   ci_type = \"confidence interval\" ) #> $ci_limits #> [1] 1 3 #>  #> $ci #> [1] 95 #>  #> $ci_type #> [1] \"confidence interval\" #>   # example for multiple parameters # lengh of list should match number of parameters list(   shape = create_epidist_uncertainty(     ci_limits = c(1, 3),     ci = 95,     ci_type = \"confidence interval\"   ),   scale = create_epidist_uncertainty(     ci_limits = c(2, 4),     ci = 95,     ci_type = \"confidence interval\"   ) ) #> $shape #> $shape$ci_limits #> [1] 1 3 #>  #> $shape$ci #> [1] 95 #>  #> $shape$ci_type #> [1] \"confidence interval\" #>  #>  #> $scale #> $scale$ci_limits #> [1] 2 4 #>  #> $scale$ci #> [1] 95 #>  #> $scale$ci_type #> [1] \"confidence interval\" #>  #>   # example with unknown uncertainty # the function can be called without arguments create_epidist_uncertainty() #> $ci_limits #> [1] NA #>  #> $ci #> [1] NA NA #>  #> $ci_type #> [1] NA #>  # or give NA as the first argument create_epidist_uncertainty(NA) #> $ci_limits #> [1] NA #>  #> $ci #> [1] NA NA #>  #> $ci_type #> [1] NA #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":null,"dir":"Reference","previous_headings":"","what":"Discretises a continuous distribution in an <epidist> object — discretise","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"Discretises continuous distribution <epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"","code":"discretise(x, ...)  discretize(x, ...)  # S3 method for epidist discretise(x, ...)  # S3 method for default discretise(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"x <epidist> object. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"Converts S3 distribution object <epidist> continuous (using object {distributional} package) discretised distribution (using object {distcrete} package).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"","code":"ebola_incubation <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing discretise(ebola_incubation) #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: discrete gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise distribution parameters — .clean_epidist_params","title":"Standardise distribution parameters — .clean_epidist_params","text":".clean_epidist_params() dispatches distribution specific parameter cleaning function depending prob_dist. example prob_dist = \"gamma\" call .clean_epidist_params_gamma().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise distribution parameters — .clean_epidist_params","text":"","code":".clean_epidist_params(prob_dist, prob_dist_params)  .clean_epidist_params_gamma(prob_dist_params)  .clean_epidist_params_lnorm(prob_dist_params)  .clean_epidist_params_nbinom(prob_dist_params)  .clean_epidist_params_geom(prob_dist_params)  .clean_epidist_params_pois(prob_dist_params)  .clean_epidist_params_norm(prob_dist_params)  .clean_epidist_params_exp(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise distribution parameters — .clean_epidist_params","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise distribution parameters — .clean_epidist_params","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Standardise distribution parameters — .clean_epidist_params","text":"Calling is_epidist_params() start .clean_epidist_params() ensures parameterisation incorrect error early dispatch distribution specific cleaning functions (e.g. .clean_epidist_params_gamma()). means distribution specific parameter cleaning functions need check error incorrect parameterisation.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the variables input by users — .clean_string","title":"Standardise the variables input by users — .clean_string","text":"Checks user supplied character string converts epiparameter standards: lower-case whitespace instead dashes underscores. Examples strings needing cleaned : disease pathogen names, epidemiological distributions.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the variables input by users — .clean_string","text":"","code":".clean_string(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the variables input by users — .clean_string","text":"x character string.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the variables input by users — .clean_string","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"Convert shape scale parameters gamma distribution number summary statistics can calculated analytically given gamma parameters. One exception median calculated using qgamma() analytical form available.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"","code":".convert_params_gamma(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"Convert probability (prob) geometric distribution number summary statistics can calculated analytically given geometric parameter. One exception median calculated using stats::qgeom() analytical form always unique.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"","code":".convert_params_geom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"conversion function assumes distribution represents number failures first success (supported zero). form used base R distributional::dist_geometric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":null,"dir":"Reference","previous_headings":"","what":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"Converts meanlog sdlog parameters lognormal distribution number summary statistics can calculated analytically given lognormal parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"","code":".convert_params_lnorm(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"Convert probability (prob) dispersion parameters negative binomial distribution number summary statistics can calculated analytically given negative binomial parameters. One exception median calculated using qnbinom() analytical form available. parameters prob dispersion (also commonly represented r).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"","code":".convert_params_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, ex_kurtosis.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"Convert shape scale parameters Weibull distribution number summary statistics can calculated analytically given Weibull parameters. Note conversion uses gamma() function.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"","code":".convert_params_weibull(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"Convert summary statistics input shape scale parameters gamma distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"","code":".convert_summary_stats_gamma(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"list two elements, shape scale","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"Convert summary statistics geometric distribution parameter (prob) geometric distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"","code":".convert_summary_stats_geom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"list one element, probability parameter.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"conversion function assumes distribution represents number failures first success (supported zero). form used base R distributional::dist_geometric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"Convert summary statistics input meanlog sdlog parameters lognormal distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"","code":".convert_summary_stats_lnorm(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"list two elements: meanlog sdlog","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"Convert summary statistics negative binomial distribution parameters (prob) (dispersion) negative binomial distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"","code":".convert_summary_stats_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"list two elements, probability dispersion parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"Convert summary statistics input shape scale parameters Weibull distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"","code":".convert_summary_stats_weibull(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"list two elements, shape scale.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"Optimises parameters specified probability distribution given percentiles distribution values percentiles, median range sample number samples.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"","code":".extract_param(values, distribution, percentiles, samples)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"values vector. type = percentiles: c(percentile_1, percentile_2); type = range: c(median, min, max). distribution character specifying distribution use. Default lnorm; also takes gamma, weibull norm. percentiles vector two elements specifying percentiles defined values using type = \"percentiles\". Percentiles specified 0 1. example 2.5th 97.5th percentile given c(0.025, 0.975). samples numeric specifying sample size using type = \"range\".","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"list output stats::optim().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an <epidist> object — epidist","title":"Create an <epidist> object — epidist","text":"<epidist> class used store epidemiological parameters single disease. epidemiological parameters cover variety aspects including delay distributions (e.g. incubation periods serial intervals, among others) offspring distributions. <epidist> object functional unit provided {epiparameter} plug epidemiological pipelines. Obtaining <epidist> object can achieved two main ways: epidemiological distribution stored {epiparameter} library can accessed epidist_db(). alternative method information (e.g. disease distribution parameter estimates) like input <epidist> object order work existing analysis pipelines. epidist() function can used fill field information known.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an <epidist> object — epidist","text":"","code":"epidist(   disease,   pathogen = NA_character_,   epi_dist,   prob_distribution = NA_character_,   prob_distribution_params = NA_real_,   uncertainty = create_epidist_uncertainty(),   summary_stats = create_epidist_summary_stats(),   auto_calc_params = TRUE,   citation = create_epidist_citation(),   metadata = create_epidist_metadata(),   method_assess = create_epidist_method_assess(),   discretise = FALSE,   truncation = NA_real_,   notes = NULL,   ... )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an <epidist> object — epidist","text":"disease character string name infectious disease. pathogen character string name causative agent disease, NA known. epi_dist character string name epidemiological distribution type. prob_distribution character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_distribution_params named vector probability distribution parameters. uncertainty list named vectors uncertainty around probability distribution parameters. uncertainty around parameter estimates unknown use create_epidist_uncertainty() (argument default) create list correct names missing values. summary_stats list summary statistics, use create_epidist_summary_stats() create list. list can include summary statistics inferred distribution mean standard deviation, quantiles distribution, information data used fit distribution lower upper range. summary statistics can also include uncertainty around metrics confidence interval around mean standard deviation. auto_calc_params boolean logical determining whether try calculate probability distribution parameters summary statistics distribution parameters provided. Default TRUE. case sufficient summary statistics provided parameter(s) distribution , calc_dist_params() function called calculate parameters add epidist object created. citation character string citation source data paper inferred distribution parameters, use create_epidist_citation() create citation. metadata list metadata, can include: sample size, transmission mode disease (e.g. vector-borne directly transmitted), etc. assumed disease vector-borne distribution intrinsic (e.g. extrinsic delay distribution extrinsic incubation period) unless transmission_mode = \"vector_borne\" contained metadata. Use create_epidist_metadata() create metadata. method_assess list methodological aspects used fitting distribution, use create_epidist_method_assess() create method assessment. discretise boolean logical whether distribution discretised. Default FALSE assumes continuous probability distribution truncation numeric specifying truncation point inferred distribution truncated, NA unknown. notes character string additional information data, inference method disease. ... dots Extra arguments passed internal functions. commonly used pass arguments distcrete::distcrete() construct discretised distribution S3 object. see arguments can adjusted discretised distributions see distcrete::distcrete().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an <epidist> object — epidist","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an <epidist> object — epidist","text":"Accepted <epidist> distribution parameterisations : Gamma must either 'shape' 'scale' 'shape' 'rate' Weibull must 'shape' 'scale' Lognormal must 'meanlog' 'sdlog' 'mu' 'sigma' Negative Binomial must either 'mean' 'dispersion' 'n' 'p' Geometric must either 'mean' 'prob' Poisson must 'mean'","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an <epidist> object — epidist","text":"","code":"# minimal input required for `epidist` ebola_incubation <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing  # minimal input required for discrete `epidist` ebola_incubation <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1),   discretise = TRUE ) #> Citation cannot be created as author, year, journal or title is missing  # example with more fields filled in ebola_incubation <- epidist(   disease = \"ebola\",   pathogen = \"ebola_virus\",   epi_dist = \"incubation\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1),   uncertainty = create_epidist_uncertainty(),   summary_stats = create_epidist_summary_stats(     mean = 2,     sd = 1   ),   citation = create_epidist_citation(     author = person(given = \"John\", family = \"Smith\"),     year = 2002,     title = \"COVID-19 incubation period\",     journal = \"Epi Journal\",     doi = \"10.19832/j.1366-9516.2012.09147.x\"   ),   metadata = create_epidist_metadata(     sample_size = 10,     region = \"UK\",     transmission_mode = \"natural_human_to_human\",     inference_method = \"MLE\"   ),   method_assess = create_epidist_method_assess(     censored = TRUE   ),   discretise = FALSE,   truncation = NA,   notes = \"No notes\" ) #> Using Smith J (2002). “COVID-19 incubation period.” _Epi Journal_. #> doi:10.19832/j.1366-9516.2012.09147.x #> <https://doi.org/10.19832/j.1366-9516.2012.09147.x>.  #> To retrieve the citation use the 'get_citation' function"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":null,"dir":"Reference","previous_headings":"","what":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"Extract <epidist> object(s) directly library epidemiological parameters. epiparameter library epidemiological parameters compiled primary literature sources. list output epidist_db() can subset data contains, example : disease, pathogen, epidemiological distribution, sample size, region, etc. distribution specific study required, author argument can specified. Multiple entries (<epidist> objects) can returned, use arguments subset entries use single_epidist = TRUE force single <epidist> returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"","code":"epidist_db(   disease = \"all\",   pathogen = \"all\",   epi_dist = \"all\",   author = NULL,   subset = NULL,   single_epidist = FALSE )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"disease character string specifying disease. pathogen character string specifying pathogen. epi_dist character string specifying epidemiological distribution. See details full list epidemiological distributions. author character string specifying author study reporting distribution. first author matched. recommended use family name first names may may initialised. subset Either NULL valid R expressions evaluates logicals subset list <epidist>, function can applied list <epidist> objects. Subsetting (using subset) can combined subsetting done disease epidist arguments (author specified). left NULL (default) subsetting carried . subset argument similar subsetting <data.frame>, difference fixed comparisons vectorised comparisons needed. example sample_size > 10 valid subset expression, sample_size == max(sample_size), valid subset expression <data.frame> work. vectorised expression often error, likely return unexpected results. sample_size == max(sample_size) example always return TRUE (except NAs) single numeric equal max value. expression specified without using data object name (e.g. df$var) instead just var supplied. words, argument uses non-standard evaluation, just subset argument subset(), similar <data-masking> used dplyr package. single_epidist boolean logical determining whether single <epidist> multiple entries library can returned matched arguments (disease, epi_dist, author). argument used prevent multiple sets parameters returned one wanted. Note: multiple entries match arguments supplied single_epidist = TRUE <epidist> parameterised (accounts truncation available) largest sample size returned (see is_parameterised()). multiple entries equal sorting first entry returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"<epidist> object list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"disease, epi_dist author given individual arguments common variables subset parameter library . subset argument facilitates subsetting rows select <epidist> object(s) desired. subset based multiple variables separate expression &. List epidemiological distributions: \"\" (default, returns entries library) \"incubation period\" \"onset hospitalisation\" \"onset death\" \"serial interval\" \"generation time\" \"offspring distribution\" \"hospitalisation death\" \"hospitalisation discharge\" \"notification death\" \"notification discharge\" \"onset discharge\" \"onset ventilation\"","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"","code":"epidist_db(disease = \"influenza\", epi_dist = \"serial_interval\") #> Returning 1 results that match the criteria (1 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function #> Disease: Influenza #> Pathogen: Influenza-A-H1N1Pdm #> Epi Distribution: serial interval #> Study: Ghani A, Baguelin M, Griffin J, Flasche S, van Hoek A, Cauchemez S, #> Donnelly C, Robertson C, White M, Truscott J, Fraser C, Garske T, White #> P, Leach S, Hall I, Jenkins H, Ferguson N, Cooper B (2009). “The Early #> Transmission Dynamics of H1N1pdm Influenza in the United Kingdom.” #> _PLoS Currents_. doi:10.1371/currents.RRN1130 #> <https://doi.org/10.1371/currents.RRN1130>. #> Distribution: gamma #> Parameters: #>   shape: 2.622 #>   scale: 0.957  # example using custom subsetting eparam <- epidist_db(   disease = \"SARS\",   epi_dist = \"offspring_distribution\",   subset = sample_size > 40 ) #> Returning 1 results that match the criteria (1 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function  # example using functional subsetting eparam <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation_period\",   subset = is_parameterised ) #> Returning 11 results that match the criteria (11 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function  # example forcing a single <epidist> to be returned eparam <- epidist_db(   disease = \"SARS\",   epi_dist = \"offspring_distribution\",   single_epidist = TRUE ) #> Using Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>..  #> To retrieve the citation use the 'get_citation' function"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"Convert <data.frame> .data.frame.epidist() <epidist>","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"","code":"epidist_df_to_epidist(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"x <data.frame>. ... dots Extra arguments pass epidist().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":null,"dir":"Reference","previous_headings":"","what":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"<epidist> object holds probability distribution can either continuous discrete distribution. density, cumulative distribution, quantile random number generation functions. operate distribution can included <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"","code":"# S3 method for epidist density(x, at, ...)  # S3 method for epidist cdf(x, q, ..., log = FALSE)  # S3 method for epidist quantile(x, p, ...)  # S3 method for epidist generate(x, times, ...)  # S3 method for vb_epidist density(x, at, ...)  # S3 method for vb_epidist cdf(x, q, ...)  # S3 method for vb_epidist quantile(x, p, ...)  # S3 method for vb_epidist generate(x, times, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"x <epidist> <vb_epidist> object. quantiles evaluate . ... dots Extra arguments passed method. q quantiles evaluate . log TRUE, probabilities given log probabilities. p probabilities evaluate . times number random samples.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"<epidist> object given numeric vector returned, <vb_epidist> object given list two elements numeric vector returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing  # example of each distribution method for an `epidist` object stats::density(edist, at = 1) #> [1] 0.3678794 distributional::cdf(edist, q = 1) #> [1] 0.6321206 stats::quantile(edist, p = 0.2) #> [1] 0.2231436 distributional::generate(edist, times = 10) #>  [1] 3.56720380 1.16790186 0.05745463 0.34040705 3.47156091 1.04366207 #>  [7] 3.02627506 0.36756952 0.09970044 0.78957870  vb_edist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(transmission_mode = \"vector_borne\")   ),   extrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = TRUE     )   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing  # example of each distribution method for an `vb_epidist` object stats::density(vb_edist, at = 1) #> $intrinsic #> [1] 0.3678794 #>  #> $extrinsic #> [1] 0.3678794 #>  distributional::cdf(vb_edist, q = 1) #> $intrinsic #> [1] 0.6321206 #>  #> $extrinsic #> [1] 0.6321206 #>  stats::quantile(vb_edist, p = 0.2) #> $intrinsic #> [1] 0.2231436 #>  #> $extrinsic #> [1] 0.2231436 #>  distributional::generate(vb_edist, times = 10) #> $intrinsic #>  [1] 0.003006878 3.549754306 0.320788501 0.057208557 1.192544692 0.977676517 #>  [7] 0.270517553 0.632583351 0.687157296 2.307000169 #>  #> $extrinsic #>  [1] 0.5823610 0.4097386 0.4414623 0.3029223 0.3143513 0.1501912 1.9871448 #>  [8] 0.0957137 4.3464560 0.5334439 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter-package.html","id":null,"dir":"Reference","previous_headings":"","what":"epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes — epiparameter-package","title":"epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes — epiparameter-package","text":"Library epidemiological parameters infectious diseases set classes helper functions.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes — epiparameter-package","text":"Maintainer: Joshua W. Lambert joshua.lambert@lshtm.ac.uk (ORCID) [copyright holder] Authors: Adam Kucharski adam.kucharski@lshtm.ac.uk (ORCID) [copyright holder] Carmen Tamayo carmen.tamayo-cuartero@lshtm.ac.uk (ORCID) contributors: Hugo Gruson hugo.gruson@data.org (ORCID) [contributor, reviewer] Sebastian Funk sebastian.funk@lshtm.ac.uk (ORCID) [contributor] Pratik Gupte pratik.gupte@lshtm.ac.uk (ORCID) [reviewer]","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":null,"dir":"Reference","previous_headings":"","what":"Package options — epiparameter_options","title":"Package options — epiparameter_options","text":"Options modify printing epiparameter objects. Currently options used modify printing <multi_epidist> class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Package options — epiparameter_options","text":"","code":"epiparameter_options"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Package options — epiparameter_options","text":"object class list length 2.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Package options — epiparameter_options","text":"Options set options() retrieved getOption(). options changed epiparameter package need reloaded new options taken account. Options can set .Rprofile persist across R sessions.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":null,"dir":"Reference","previous_headings":"","what":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"subset data World Health Organization Global Tuberculosis Report ...","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"","code":"epireview_core_cols"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":"epireview-core-cols","dir":"Reference","previous_headings":"","what":"epireview_core_cols","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"character vector 56 elements data taken intersection column names disease parameter tables epireview R package.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"https://github.com/mrc-ide/epireview","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"Summary data distributions, provided reports meta-analyses, can used extract parameters chosen distribution. Currently available distributions : lognormal, gamma, Weibull normal. Extracting lognormal returns meanlog sdlog parameters, extracting gamma Weibull returns shape scale parameters, extracting normal returns mean sd parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"","code":"extract_param(   type = c(\"percentiles\", \"range\"),   values,   distribution = c(\"lnorm\", \"gamma\", \"weibull\", \"norm\"),   percentiles,   samples,   control = list(max_iter = 1000, tolerance = 1e-05) )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"type character defining whether summary statistics based around percentiles (default) range. values vector. type = percentiles: c(percentile_1, percentile_2); type = range: c(median, min, max). distribution character specifying distribution use. Default lnorm; also takes gamma, weibull norm. percentiles vector two elements specifying percentiles defined values using type = \"percentiles\". Percentiles specified 0 1. example 2.5th 97.5th percentile given c(0.025, 0.975). samples numeric specifying sample size using type = \"range\". control named list containing options optimisation. List element $max_iter numeric specifying maximum number times parameter extraction run optimisation returning result early. prevents overly long optimisation loops optimisation unstable converge multiple iterations. Default 1000 iterations. List element $tolerance passed check_optim_conv() tolerance parameter convergence iterations optimisation. Elements control list passed optim().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"named numeric vector parameter values distribution. distribution = lnorm parameters returned meanlog sdlog; distribution = gamma distribution = weibull parameters returned shape scale; distribution = norm parameters returned mean sd.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"gamma, lnorm weibull, extract_param() works strictly positive values percentiles distribution median range data (numerics supplied values argument). means negative values lower percentile lower range work function although may present epidemiological data (e.g. negative serial interval). norm distribution negative values allowed.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"Adam Kucharski, Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"","code":"# set seed to control for stochasticity set.seed(1)  # extract parameters of a lognormal distribution from the 75 percentiles extract_param(   type = \"percentiles\",   values = c(6, 13),   distribution = \"lnorm\",   percentiles = c(0.125, 0.875) ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>   meanlog     sdlog  #> 2.1783557 0.3360688   # extract parameters of a gamma distribution from median and range extract_param(   type = \"range\",   values = c(10, 3, 18),   distribution = \"gamma\",   samples = 20 ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>    shape    scale  #> 5.342206 1.994304"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":null,"dir":"Reference","previous_headings":"","what":"Function for extracting distribution parameters — extraction_functions","title":"Function for extracting distribution parameters — extraction_functions","text":"Set functions can used estimate parameters distribution (lognormal, gamma, Weibull, normal) via optimisation either percentiles median ranges.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function for extracting distribution parameters — extraction_functions","text":"","code":"fit_range(param, val, dist = c(\"lnorm\", \"gamma\", \"weibull\", \"norm\"))  fit_percentiles(param, val, dist = c(\"lnorm\", \"gamma\", \"weibull\", \"norm\"))"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function for extracting distribution parameters — extraction_functions","text":"param Named numeric vector distribution parameters optimised. val Numeric vector, case using percentiles contains values percentiles percentiles, case median range contains median, lower range, upper range number sample points evaluate function . dist character string name distribution fitting. Naming follows base R distribution names (e.g. lnorm lognormal).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Function for extracting distribution parameters — extraction_functions","text":"Adam Kucharski, Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Family method for the <epidist> class — family.epidist","title":"Family method for the <epidist> class — family.epidist","text":"family() function used extract distribution names objects {distributional} {distcrete}. method provides interface <epidist> objects give consistent output irrespective internal distribution class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Family method for the <epidist> class — family.epidist","text":"","code":"# S3 method for epidist family(object, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Family method for the <epidist> class — family.epidist","text":"object <epidist> object. ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Family method for the <epidist> class — family.epidist","text":"character string name distribution, NA <epidist> object unparameterised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Family method for the <epidist> class — family.epidist","text":"","code":"# example with continuous distribution edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing family(edist) #> [1] \"gamma\"  # example with discretised distribution edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1),   discretise = TRUE ) #> Citation cannot be created as author, year, journal or title is missing family(edist) #> [1] \"lnorm\""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Format method for <epidist> class — format.epidist","title":"Format method for <epidist> class — format.epidist","text":"Format method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format method for <epidist> class — format.epidist","text":"","code":"# S3 method for epidist format(x, header = TRUE, vb = NULL, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format method for <epidist> class — format.epidist","text":"x <epidist> object. header Boolean logical determining whether header (first part) print method printed. used internally plotting vb_epidist class vb Either NULL (default) character string either \"Intrinsic\" \"Extrinsic\" used internally plotting vb_epidist class ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for <epidist> class — format.epidist","text":"Invisibly returns <epidist>. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format method for <epidist> class — format.epidist","text":"","code":"epidist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing format(epidist) #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Format method for <vb_epidist> class — format.vb_epidist","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"Format method <vb_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"","code":"# S3 method for vb_epidist format(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"x <vb_epidist> object. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"Invisibly returns <vb_epidist>. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"","code":"vb_epidist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ),   extrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing #> Warning: Distributions in vb_epidist class are not vector-borne. Check metadata #> Warning: The extrinsic distribution is not specified extrinsic. Check metadata format(vb_epidist) #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #>  #>  <Intrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000 #>  #>  <Extrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Get citation from an <epidist> object — get_citation.epidist","title":"Get citation from an <epidist> object — get_citation.epidist","text":"Extract citation stored <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get citation from an <epidist> object — get_citation.epidist","text":"","code":"# S3 method for epidist get_citation(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get citation from an <epidist> object — get_citation.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get citation from an <epidist> object — get_citation.epidist","text":"<bibentry> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get citation from an <epidist> object — get_citation.epidist","text":"","code":"# example with <epidist> edist <- epidist_db(single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function get_citation(edist) #> Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>.  # example returning bibtex format edist <- epidist_db(disease = \"COVID-19\", single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function cit <- get_citation(edist) format(cit, style = \"bibtex\") #> [1] \"@Article{,\\n  author = {Natalie M. Linton and Tetsuro Kobayashi and Yichi Yang and Katsuma Hayashi and Andrei R. Akhmetzhanov and Sung-mok Jung and Baoyin Yuan and Ryo Kinoshita and Hiroshi Nishiura},\\n  year = {2020},\\n  title = {Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data},\\n  journal = {Journal of Clinical Medicine},\\n  doi = {10.3390/jcm9020538},\\n  pmid = {32079150},\\n}\""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Get citation from an object — get_citation","title":"Get citation from an object — get_citation","text":"Extract citation stored R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get citation from an object — get_citation","text":"","code":"get_citation(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get citation from an object — get_citation","text":"x object used select method. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"Extract citation stored list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"","code":"# S3 method for multi_epidist get_citation(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"<bibentry> object containing multiple references. length output <bibentry> equal length list <epidist> objects supplied.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"","code":"# example with list of <epidist> edist <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function get_citation(edist) #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-9 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-9>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-10 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-10>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-11 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-11>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-12 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-12>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-13 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-13>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-14 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-14>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-15 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-15>. #>  #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 <https://doi.org/10.1002/sim.3659>. #>  #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 <https://doi.org/10.1002/sim.3659>. #>  #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 <https://doi.org/10.1002/sim.3659>. #>  #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 <https://doi.org/10.1002/sim.3659>. #>  #> Nishiura H, Inaba H (2011). “Estimation of the incubation period of #> influenza A (H1N1-2009) among imported cases: addressing censoring #> using outbreak data at the origin of importation.” _Journal of #> Theoretical Biology_. doi:10.1016/j.jtbi.2010.12.017 #> <https://doi.org/10.1016/j.jtbi.2010.12.017>. #>  #> Nishiura H, Inaba H (2011). “Estimation of the incubation period of #> influenza A (H1N1-2009) among imported cases: addressing censoring #> using outbreak data at the origin of importation.” _Journal of #> Theoretical Biology_. doi:10.1016/j.jtbi.2010.12.017 #> <https://doi.org/10.1016/j.jtbi.2010.12.017>. #>  #> Virlogeux V, Li M, Tsang T, Feng L, Fang V, Jiang H, Wu P, Zheng J, Lau #> E, Cao Y, Qin Y, Liao Q, Yu H, Cowling B (2015). “Estimating the #> Distribution of the Incubation Periods of Human Avian Influenza 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S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). “West African Ebola #> Epidemic after One Year — Slowing but Not Yet under Control.” _The New #> England Journal of Medicine_. doi:10.1056/NEJMc1414992 #> <https://doi.org/10.1056/NEJMc1414992>. #>  #> WHO Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Blake I, #> Brennan R, Cori A, Donnelly C, Dorigatti I, Dye C, Eckmanns T, Ferguson #> N, Formenty P, Fraser C, Garcia E, Garske T, Hinsley W, Holmes D, #> Hugonnet S, Iyengar S, Jombart T, Krishnan R, Meijers S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). “West African Ebola #> Epidemic after One Year — Slowing but Not Yet under Control.” _The New #> England Journal of Medicine_. doi:10.1056/NEJMc1414992 #> <https://doi.org/10.1056/NEJMc1414992>. #>  #> WHO Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Blake I, #> Brennan R, Cori A, Donnelly C, Dorigatti I, Dye C, Eckmanns T, Ferguson #> N, Formenty P, Fraser C, Garcia E, Garske T, Hinsley W, Holmes D, #> Hugonnet S, Iyengar S, Jombart T, Krishnan R, Meijers S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). “West African Ebola #> Epidemic after One Year — Slowing but Not Yet under Control.” _The New #> England Journal of Medicine_. doi:10.1056/NEJMc1414992 #> <https://doi.org/10.1056/NEJMc1414992>. #>  #> WHO Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Blake I, #> Brennan R, Cori A, Donnelly C, Dorigatti I, Dye C, Eckmanns T, Ferguson #> N, Formenty P, Fraser C, Garcia E, Garske T, Hinsley W, Holmes D, #> Hugonnet S, Iyengar S, Jombart T, Krishnan R, Meijers S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). “West African Ebola #> Epidemic after One Year — Slowing but Not Yet under Control.” _The New #> England Journal of Medicine_. doi:10.1056/NEJMc1414992 #> <https://doi.org/10.1056/NEJMc1414992>. #>  #> WHO Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Blake I, #> Brennan R, Cori A, Donnelly C, Dorigatti I, Dye C, Eckmanns T, Ferguson #> N, Formenty P, Fraser C, Garcia E, Garske T, Hinsley W, Holmes D, #> Hugonnet S, Iyengar S, Jombart T, Krishnan R, Meijers S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). “West African Ebola #> Epidemic after One Year — Slowing but Not Yet 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doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wei F, Peng Z, Jin Z, Wang J, Xu X, Zhang X, Xu J, Ren Z, Bai Y, Wang #> X, Lu B, Wang Z, Xu J, Huang S (2022). “Study and prediction of the #> 2022 global monkeypox epidemic.” _Journal of Biosafety and #> Biosecurity_. doi:10.1016/j.jobb.2022.12.001 #> <https://doi.org/10.1016/j.jobb.2022.12.001>. #>  #> Wei F, Peng Z, Jin Z, Wang J, Xu X, Zhang X, Xu J, Ren Z, Bai Y, Wang #> X, Lu B, Wang Z, Xu J, Huang S (2022). “Study and prediction of the #> 2022 global monkeypox epidemic.” _Journal of Biosafety and #> Biosecurity_. doi:10.1016/j.jobb.2022.12.001 #> <https://doi.org/10.1016/j.jobb.2022.12.001>. #>  #> Wei F, Peng Z, Jin Z, Wang J, Xu X, Zhang X, Xu J, Ren Z, Bai Y, Wang #> X, Lu B, Wang Z, Xu J, Huang S (2022). “Study and prediction of the #> 2022 global monkeypox epidemic.” _Journal of Biosafety and #> Biosecurity_. doi:10.1016/j.jobb.2022.12.001 #> <https://doi.org/10.1016/j.jobb.2022.12.001>."},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Get parameters from an <epidist> object — get_parameters.epidist","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"Extract parameters distribution stored <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"","code":"# S3 method for epidist get_parameters(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"named vector parameters NA <epidist> object unparameterised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"<epidist> object can unparameterised lacks probability distribution parameters probability distribution, case get_parameters.epidist() method return NA.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"","code":"edist <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"serial interval\",   single_epidist = TRUE ) #> Using Nishiura H, Linton N, Akhmetzhanov A (2020). “Serial interval of novel #> coronavirus (COVID-19) infections.” _International Journal of #> Infectious Diseases_. doi:10.1016/j.ijid.2020.02.060 #> <https://doi.org/10.1016/j.ijid.2020.02.060>..  #> To retrieve the citation use the 'get_citation' function get_parameters(edist) #>   meanlog     sdlog  #> 1.3862617 0.5679803"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":null,"dir":"Reference","previous_headings":"","what":"Get parameters from an object — get_parameters","title":"Get parameters from an object — get_parameters","text":"Extract parameters stored R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get parameters from an object — get_parameters","text":"","code":"get_parameters(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get parameters from an object — get_parameters","text":"x object used select method. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"Parameters probability distribution can extracted using values given percentiles distribution percentiles using extract_param(). get_percentiles() takes named vector percentiles (names) values percentiles (elements vector) selects two values lower upper percentiles used extraction. lower upper percentile available NA returned. also formats vector names can correctly converted numeric using .numeric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"","code":"get_percentiles(percentiles)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"percentiles named vector values percentiles names percentiles. See Details accepted vector name format.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"named numeric vector percentiles.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"name format character value percentile. Numbers decimal places decimal point name. example 5th 95th percentile can given   2.5th 97.5th percentile can given ","code":"get_percentiles(c(\"5\" = 1, \"95\" = 10)) get_percentiles(c(\"2.5\" = 1, \"97.5\" = 10))"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"Get lower upper percentiles preference symmetrical percentiles","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"","code":"get_sym_percentiles(percentiles)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"percentiles named vector percentiles. names correct format converted numeric value using .numeric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"named numeric vector two elements lower (first element) upper (second element) percentiles.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if distribution in <epidist> is continuous — is_continuous","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"Check distribution <epidist> continuous","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"","code":"is_continuous(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"x <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"<epidist> class can hold <distribution> <distcrete> probability distribution objects distributional package distcrete package, respectively. <distribution> objects can continuous discrete distributions (e.g. gamma negative binomial), <distcrete> objects discrete.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1) ) #> Citation cannot be created as author, year, journal or title is missing is_continuous(edist) #> [1] TRUE is_continuous(discretise(edist)) #> [1] FALSE  edist <- epidist(   disease = \"ebola\",   epi_dist = \"offspring distribution\",   prob_distribution = \"nbinom\",   prob_distribution_params = c(mean = 2, dispersion = 0.5) ) #> Citation cannot be created as author, year, journal or title is missing is_continuous(edist) #> [1] FALSE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is an <epidist> — is_epidist","title":"Check object is an <epidist> — is_epidist","text":"Check object <epidist>","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check object is an <epidist> — is_epidist","text":"","code":"is_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check object is an <epidist> — is_epidist","text":"x R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check object is an <epidist> — is_epidist","text":"boolean logical, TRUE object <epidist> FALSE .","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check object is an <epidist> — is_epidist","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"serial_interval\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing  is_epidist(edist) #> [1] TRUE  false_edist <- list(   disease = \"ebola\",   epi_dist = \"serial_interval\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) )  is_epidist(false_edist) #> [1] FALSE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"Check <data.frame> input .data.frame.epidist()","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"","code":"is_epidist_df(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"x <data.frame>.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"single logical boolean.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"Check whether vector parameters probability distribution set possible parameters used epiparameter package","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"","code":"is_epidist_params(prob_dist, prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"check valid parameters independent whether distribution truncated discretised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"","code":"is_epidist_params(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 2, scale = 1) ) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if <data.frame> input is from epireview — is_epireview","title":"Check if <data.frame> input is from epireview — is_epireview","text":"Check <data.frame> input epireview","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if <data.frame> input is from epireview — is_epireview","text":"","code":"is_epireview(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if <data.frame> input is from epireview — is_epireview","text":"x <data.frame>.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if <data.frame> input is from epireview — is_epireview","text":"single logical boolean.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"Check <epidist> list <epidist> objects contains distribution distribution parameters","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"","code":"is_parameterised(x, ...)  is_parameterized(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"x <epidist> list <epidist> objects. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"single boolean logical <epidist> vector logicals equal length list <epidist> objects input. <epidist> object missing either probability distribution parameters probability distribution returns FALSE, otherwise returns TRUE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"","code":"# parameterised <epidist> edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing is_parameterised(edist) #> [1] TRUE  # unparameterised <epidist> edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation\" ) #> Citation cannot be created as author, year, journal or title is missing #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object is_parameterised(edist) #> [1] FALSE  # list of <epidist> edist <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function is_parameterised(edist) #>   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE  TRUE #>  [25]  TRUE  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [49]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [61]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [73]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE #>  [85] FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE #>  [97]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #> [109]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE #> [121] FALSE FALSE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if distribution in <epidist> is truncated — is_truncated","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"Check distribution <epidist> truncated","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"","code":"is_truncated(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"x <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"<epidist> class can hold probability distribution objects {distributional} package {distcrete} package, however, distribution objects {distributional} can truncated. <epidist> object <distcrete> object is_truncated return FALSE default.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1) ) #> Citation cannot be created as author, year, journal or title is missing is_truncated(edist) #> [1] FALSE  edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1),   truncation = 10 ) #> Citation cannot be created as author, year, journal or title is missing is_truncated(edist) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is a <vb_epidist> — is_vb_epidist","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"Check object <vb_epidist>","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"","code":"is_vb_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"x R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"boolean logical, TRUE object <vb_epidist> FALSE .","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"","code":"vb_edist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(transmission_mode = \"vector_borne\")   ),   extrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = TRUE     )   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing  is_vb_epidist(vb_edist) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Mean method for <epidist> class — mean.epidist","title":"Mean method for <epidist> class — mean.epidist","text":"Mean method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mean method for <epidist> class — mean.epidist","text":"","code":"# S3 method for epidist mean(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mean method for <epidist> class — mean.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mean method for <epidist> class — mean.epidist","text":"numeric mean distribution NA.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Mean method for <epidist> class — mean.epidist","text":"","code":"edist <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function mean(edist) #> [1] 5.6"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for <epidist> class — new_epidist","title":"Constructor for <epidist> class — new_epidist","text":"Create <epidist> object. constructor search whether parameters probability distribution supplied look see whether can inferred/extracted/ converted summary statistics provided. also convert probability distribution (prob_dist) parameters (prob_dist_params) S3 class, either distribution object {distributional} discretise = FALSE, distcrete object {distcrete} discretise = TRUE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for <epidist> class — new_epidist","text":"","code":"new_epidist(   disease = character(),   pathogen = character(),   epi_dist = character(),   prob_dist = list(),   prob_dist_params = numeric(),   uncertainty = list(),   summary_stats = list(),   auto_calc_params = logical(),   citation = character(),   metadata = list(),   method_assess = list(),   discretise = logical(),   truncation = numeric(),   notes = character(),   ... )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for <epidist> class — new_epidist","text":"disease character string name infectious disease. pathogen character string name causative agent disease, NA known. epi_dist character string name epidemiological distribution type. prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters. uncertainty list named vectors uncertainty around probability distribution parameters. uncertainty around parameter estimates unknown use create_epidist_uncertainty() (argument default) create list correct names missing values. summary_stats list summary statistics, use create_epidist_summary_stats() create list. list can include summary statistics inferred distribution mean standard deviation, quantiles distribution, information data used fit distribution lower upper range. summary statistics can also include uncertainty around metrics confidence interval around mean standard deviation. auto_calc_params boolean logical determining whether try calculate probability distribution parameters summary statistics distribution parameters provided. Default TRUE. case sufficient summary statistics provided parameter(s) distribution , calc_dist_params() function called calculate parameters add epidist object created. citation character string citation source data paper inferred distribution parameters, use create_epidist_citation() create citation. metadata list metadata, can include: sample size, transmission mode disease (e.g. vector-borne directly transmitted), etc. assumed disease vector-borne distribution intrinsic (e.g. extrinsic delay distribution extrinsic incubation period) unless transmission_mode = \"vector_borne\" contained metadata. Use create_epidist_metadata() create metadata. method_assess list methodological aspects used fitting distribution, use create_epidist_method_assess() create method assessment. discretise boolean logical whether distribution discretised. Default FALSE assumes continuous probability distribution truncation numeric specifying truncation point inferred distribution truncated, NA unknown. notes character string additional information data, inference method disease. ... dots Extra arguments passed internal functions. commonly used pass arguments distcrete::distcrete() construct discretised distribution S3 object. see arguments can adjusted discretised distributions see distcrete::distcrete().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for <epidist> class — new_epidist","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Constructor for <epidist> class — new_epidist","text":"","code":"epiparameter:::new_epidist(   disease = \"ebola\",   pathogen = \"ebola_virus\",   epi_dist = \"incubation_period\",   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   uncertainty = create_epidist_uncertainty(),   summary_stats = create_epidist_summary_stats(),   auto_calc_params = TRUE,   citation = create_epidist_citation(),   metadata = create_epidist_metadata(),   method_assess = create_epidist_method_assess(),   discretise = FALSE,   truncation = NA,   notes = \"No notes\" ) #> Citation cannot be created as author, year, journal or title is missing #> Disease: ebola #> Pathogen: ebola_virus #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for <vb_epidist> class — new_vb_epidist","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"Create <vb_epidist> object binding two <epidist> objects assigning <vb_epidist> class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"","code":"new_vb_epidist(intrinsic_epidist, extrinsic_epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"intrinsic_epidist <epidist> object. extrinsic_epidist <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"<vb_epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Table of epidemiological distributions — parameter_tbl","title":"Table of epidemiological distributions — parameter_tbl","text":"function subsets epidemiological parameter library return chosen epidemiological distribution. results returned data frame containing disease, epidemiological distribution, probability distribution, author study, year publication.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Table of epidemiological distributions — parameter_tbl","text":"","code":"parameter_tbl(   multi_epidist,   disease = \"all\",   pathogen = \"all\",   epi_dist = \"all\" )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Table of epidemiological distributions — parameter_tbl","text":"multi_epidist Either <epidist> object list <epidist> objects. disease character string name infectious disease. pathogen character string name causative agent disease, NA known. epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Table of epidemiological distributions — parameter_tbl","text":"Joshua W. Lambert, Adam Kucharski","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Table of epidemiological distributions — parameter_tbl","text":"","code":"epidist_list <- epidist_db(disease = \"COVID-19\") #> Returning 27 results that match the criteria (22 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function parameter_tbl(multi_epidist = epidist_list) #> # Parameter table: #> # A data frame:    27 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 COVID-19 SARS-Co… incubation peri… NA                Men e…  2020          59 #>  2 COVID-19 SARS-Co… incubation peri… NA                Rai e…  2022        6241 #>  3 COVID-19 SARS-Co… incubation peri… NA                Alene…  2021        1453 #>  4 COVID-19 SARS-Co… serial interval  NA                Alene…  2021        3924 #>  5 COVID-19 SARS-Co… serial interval  lnorm             Nishi…  2020          28 #>  6 COVID-19 SARS-Co… serial interval  weibull           Nishi…  2020          18 #>  7 COVID-19 SARS-Co… incubation peri… weibull           Yang …  2020         178 #>  8 COVID-19 SARS-Co… serial interval  norm              Yang …  2020         131 #>  9 COVID-19 SARS-Co… incubation peri… NA                Elias…  2021       28675 #> 10 COVID-19 SARS-Co… incubation peri… weibull           Bui e…  2020          19 #> # ℹ 17 more rows  # example filtering an existing list to incubation periods epidist_list <- epidist_db(disease = \"COVID-19\") #> Returning 27 results that match the criteria (22 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function parameter_tbl(   multi_epidist = epidist_list,   epi_dist = \"incubation period\" ) #> # Parameter table: #> # A data frame:    15 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 COVID-19 SARS-Co… incubation peri… NA                Men e…  2020          59 #>  2 COVID-19 SARS-Co… incubation peri… NA                Rai e…  2022        6241 #>  3 COVID-19 SARS-Co… incubation peri… NA                Alene…  2021        1453 #>  4 COVID-19 SARS-Co… incubation peri… weibull           Yang …  2020         178 #>  5 COVID-19 SARS-Co… incubation peri… NA                Elias…  2021       28675 #>  6 COVID-19 SARS-Co… incubation peri… weibull           Bui e…  2020          19 #>  7 COVID-19 SARS-Co… incubation peri… lnorm             McAlo…  2020        1357 #>  8 COVID-19 SARS-Co… incubation peri… lnorm             McAlo…  2020        1269 #>  9 COVID-19 SARS-Co… incubation peri… lnorm             Linto…  2020          52 #> 10 COVID-19 SARS-Co… incubation peri… lnorm             Linto…  2020         158 #> 11 COVID-19 SARS-Co… incubation peri… lnorm             Linto…  2020          52 #> 12 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020         181 #> 13 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020          99 #> 14 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020         108 #> 15 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020          73"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot method for <epidist> class — plot.epidist","title":"Plot method for <epidist> class — plot.epidist","text":"Plot <epidist> object displaying either probability mass function (PMF), (case discrete distributions) probability density function (PDF) (case continuous distributions), cumulative distribution function (CDF).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot method for <epidist> class — plot.epidist","text":"","code":"# S3 method for epidist plot(x, cumulative = FALSE, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot method for <epidist> class — plot.epidist","text":"x <epidist> object. cumulative boolean logical, default FALSE. cumulative = TRUE plots cumulative distribution function (CDF). ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot method for <epidist> class — plot.epidist","text":"default xlim argument specified distribution plotted day 0 99th quantile distribution. Alternatively, numeric vector length 2 first last day plot x-axis can supplied xlim (...).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot method for <epidist> class — plot.epidist","text":"Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot method for <epidist> class — plot.epidist","text":"","code":"# plot continuous epidist edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 2, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing plot(edist)   # plot different day range (x-axis) plot(edist, xlim = c(0, 10))   # plot CDF plot(edist, cumulative = TRUE)   # plot discrete epidist edist <- discretise(edist) plot(edist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for <epidist> class — print.epidist","title":"Print method for <epidist> class — print.epidist","text":"Print method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for <epidist> class — print.epidist","text":"","code":"# S3 method for epidist print(x, header = TRUE, vb = NULL, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for <epidist> class — print.epidist","text":"x <epidist> object. header Boolean logical determining whether header (first part) print method printed. used internally plotting <vb_epidist> class. vb character string containing whether intrinsic (\"Intrinsic\") extrinsic (\"Extrinsic\") distribution vector-borne diseases. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for <epidist> class — print.epidist","text":"Invisibly returns <epidist>. Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for <epidist> class — print.epidist","text":"","code":"epidist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing epidist #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for <multi_epidist> class — print.multi_epidist","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"Print method <multi_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"","code":"# S3 method for multi_epidist print(x, ..., n = NULL)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"x <multi_epidist> object. ... dots Extra arguments passed method. n numeric specifying many <epidist> objects print. argument passed head() list printing. Default NULL number elements print controlled package options().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"Invisibly returns <multi_epidist>. Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"","code":"# entire database db <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function db #> # List of 122 <epidist> objects #> Number of diseases: 23 #> ❯ Adenovirus ❯ COVID-19 ❯ Chikungunya ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ MERS ❯ Marburg Virus Disease ❯ Measles ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ RSV ❯ Rhinovirus ❯ Rift Valley Fever ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease #> Number of epi distributions: 12 #> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval #> [[1]] #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.247 #>   sdlog: 0.975 #>  #> [[2]] #> Disease: Human Coronavirus #> Pathogen: Human_Cov #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.742 #>   sdlog: 0.918 #>  #> [[3]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.660 #>   sdlog: 1.205 #>  #> # ℹ 119 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html  # a single disease db <- epidist_db(disease = \"Ebola\") #> Returning 17 results that match the criteria (17 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function db #> # List of 17 <epidist> objects #> Number of diseases: 1 #> ❯ Ebola Virus Disease #> Number of epi distributions: 9 #> ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ serial interval #> [[1]] #> Disease: Ebola Virus Disease #> Pathogen: Ebola Virus #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 1.500 #>   dispersion: 5.100 #>  #> [[2]] #> Disease: Ebola Virus Disease #> Pathogen: Ebola Virus-Zaire Subtype #> Epi Distribution: incubation period #> Study: Eichner M, Dowell S, Firese N (2011). “Incubation period of ebola #> hemorrhagic virus subtype zaire.” _Osong Public Health and Research #> Perspectives_. doi:10.1016/j.phrp.2011.04.001 #> <https://doi.org/10.1016/j.phrp.2011.04.001>. #> Distribution: lnorm #> Parameters: #>   meanlog: 2.487 #>   sdlog: 0.330 #>  #> [[3]] #> Disease: Ebola Virus Disease #> Pathogen: Ebola Virus-Zaire Subtype #> Epi Distribution: onset to death #> Study: The Ebola Outbreak Epidemiology Team, Barry A, Ahuka-Mundeke S, Ali #> Ahmed Y, Allarangar Y, Anoko J, Archer B, Abedi A, Bagaria J, Belizaire #> M, Bhatia S, Bokenge T, Bruni E, Cori A, Dabire E, Diallo A, Diallo B, #> Donnelly C, Dorigatti I, Dorji T, Waeber A, Fall I, Ferguson N, #> FitzJohn R, Tengomo G, Formenty P, Forna A, Fortin A, Garske T, #> Gaythorpe K, Gurry C, Hamblion E, Djingarey M, Haskew C, Hugonnet S, #> Imai N, Impouma B, Kabongo G, Kalenga O, Kibangou E, Lee T, Lukoya C, #> Ly O, Makiala-Mandanda S, Mamba A, Mbala-Kingebeni P, Mboussou F, #> Mlanda T, Makuma V, Morgan O, Mulumba A, Kakoni P, Mukadi-Bamuleka D, #> Muyembe J, Bathé N, Ndumbi Ngamala P, Ngom R, Ngoy G, Nouvellet P, Nsio #> J, Ousman K, Peron E, Polonsky J, Ryan M, Touré A, Towner R, Tshapenda #> G, Van De Weerdt R, Van Kerkhove M, Wendland A, Yao N, Yoti Z, Yuma E, #> Kalambayi Kabamba G, Mwati J, Mbuy G, Lubula L, Mutombo A, Mavila O, #> Lay Y, Kitenge E (2018). “Outbreak of Ebola virus disease in the #> Democratic Republic of the Congo, April–May, 2018: an epidemiological #> study.” _The Lancet_. doi:10.1016/S0140-6736(18)31387-4 #> <https://doi.org/10.1016/S0140-6736%2818%2931387-4>. #> Distribution: gamma #> Parameters: #>   shape: 2.400 #>   scale: 3.333 #>  #> # ℹ 14 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html  # a single epi parameter db <- epidist_db(epi_dist = \"offspring distribution\") #> Returning 10 results that match the criteria (10 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function db #> # List of 10 <epidist> objects #> Number of diseases: 6 #> ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Mpox ❯ Pneumonic Plague ❯ SARS ❯ Smallpox #> Number of epi distributions: 1 #> ❯ offspring distribution #> [[1]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 1.630 #>   dispersion: 0.160 #>  #> [[2]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 0.940 #>   dispersion: 0.170 #>  #> [[3]] #> Disease: Smallpox #> Pathogen: Smallpox-Variola-Major #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 3.190 #>   dispersion: 0.370 #>  #> # ℹ 7 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for <vb_epidist> class — print.vb_epidist","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"Print method <vb_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"","code":"# S3 method for vb_epidist print(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"x <vb_epidist> object. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"Invisibly returns <vb_epidist>. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"","code":"vb_epidist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ),   extrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing #> Warning: Distributions in vb_epidist class are not vector-borne. Check metadata #> Warning: The extrinsic distribution is not specified extrinsic. Check metadata vb_epidist #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #>  #>  <Intrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000 #>  #>  <Extrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. distributional cdf, generate","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for <epidist> class — validate_epidist","title":"Validator for <epidist> class — validate_epidist","text":"Validator <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validator for <epidist> class — validate_epidist","text":"","code":"validate_epidist(epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validator for <epidist> class — validate_epidist","text":"epidist <epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validator for <epidist> class — validate_epidist","text":"Invisibly returns <epidist>. Called side-effects (errors invalid <epidist> object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for <vb_epidist> class — validate_vb_epidist","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"Validator <vb_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"","code":"validate_vb_epidist(vb_epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"vb_epidist <vb_epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"Invisibly returns <vb_epidist>. Called side-effects (errors invalid <vb_epidist> object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a <vb_epidist> object — vb_epidist","title":"Create a <vb_epidist> object — vb_epidist","text":"<vb_epidist> class extension <epidist> class (although subclass <epidist>). used store epidemiological parameters vector-borne diseases. methods (print(), format(), plot(), generate(), cdf(), density(), quantile()) <epidist> class therefore used identically.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a <vb_epidist> object — vb_epidist","text":"","code":"vb_epidist(intrinsic_epidist, extrinsic_epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a <vb_epidist> object — vb_epidist","text":"intrinsic_epidist <epidist> object. extrinsic_epidist <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a <vb_epidist> object — vb_epidist","text":"<vb_epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a <vb_epidist> object — vb_epidist","text":"<epidist> objects contain metadata (epidist$metadata) indicating vector-borne disease (epidist$metadata$transmission_mode = \"vector_borne\") extrinsic distribution indicate metadata extrinsic distribution (epidist$metadata$extrinsic = TRUE). two aspects given construction class throw warning.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a <vb_epidist> object — vb_epidist","text":"","code":"vb <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"dengue\",     pathogen = \"dengue_virus\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = FALSE     )   ),   extrinsic_epidist = epidist(     disease = \"dengue\",     pathogen = \"dengue_virus\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 2, scale = 2),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = TRUE     )   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"epiparameter-010","dir":"Changelog","previous_headings":"","what":"epiparameter 0.1.0","title":"epiparameter 0.1.0","text":"Initial release {epiparameter} R package. {epiparameter} provides: library epidemiological parameters extracted literature range diseases. Functions classes (class methods) work epidemiological parameters distributions.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"new-features-0-1-0","dir":"Changelog","previous_headings":"","what":"New features","title":"epiparameter 0.1.0","text":"library 122 epidemiological parameter set epidemiological literature. accessible package system data (sysdata.rda, epiparameter::multi_epidist) internal data (inst/extdata/parameters.json). epidist_db() function loads epidemiological parameters library. Distribution parameter conversion extraction functions (convert_params_to_summary_stats() & convert_summary_stats_to_params(), extract_param()). S3 class work epidemiological parameters <epidist>. class S3 methods aid users easily work data structures. include printing, plotting, distribution functions PDF/PMF, CDF, random number generation distribution quantiles. <epidist> class constructor function, validator function, accessors (get_*()), checkers (is_*()). also <vb_epidist> S3 class vector-borne parameters, internal <multi_epidist> class improved printing lists <epidist> objects. package contains utility functions. list_distributions() helper function provide information list <epidist> objects tabular form. calc_disc_dist_quantile() calculates quantiles probability distribution based vector probabilities time data. Five vignettes included initial release. One introduction package (epiparameter.Rmd), one tutorial converting extracting parameters (extract_convert.Rmd), one protocol used collect entries library epidemiological parameters (data_protocol.Rmd), design vignette (design_principles.Rmd), supplementary vignette quantifies bias using parameter extraction (extract_param()) {epiparameter} (extract-bias.Rmd). Unit tests documentation files. Continuous integration workflows R package checks, rendering README.md, calculating test coverage, deploying pkgdown website, updates package citation, linting package code, checking package system dependency changes, updating copyright year, validating parameter library JSON file.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"breaking-changes-0-1-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"epiparameter 0.1.0","text":"None","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"bug-fixes-0-1-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"epiparameter 0.1.0","text":"None","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"deprecated-and-defunct-0-1-0","dir":"Changelog","previous_headings":"","what":"Deprecated and defunct","title":"epiparameter 0.1.0","text":"None","code":""}]
+[{"path":"https://epiverse-trace.github.io/epiparameter/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 epiparameter authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"converting-from-epireview-entries-into-an-epidist-object","dir":"Articles","previous_headings":"","what":"Converting from {epireview} entries into an <epidist> object","title":"Using {epireview} with {epiparameter}","text":"{epireview} package nicely provides epidemiological parameter data systematically reviewing literature, {epiparameter} provides custom data structures working epidemiological data R. Therefore, reading data {epireview} R package converting <epidist> object hopefully provide greatest utility applied outbreak analytics. start simple example reading Marburg data {epireview} converting <epidist> object using as_epidist() function {epiparameter} package. loads list four tables, specifically tibbles, contain bibliographic information ($articles), epidemiological parameters ($params), epidemiological models ($models), outbreak information ($outbreaks). start just using epidemiological parameter table convert information <epidist>. Given currently delay distributions supported conversion (feature still active development) filter include . select second entry, incubation period, use first example: can simply pass epidemiological parameter set as_epidist() conversion. resulting <epidist> contain parameterised probability distribution, instead contains range incubation period ($summary_stats), $metadata shows single case South Africa.","code":"marburg_data <- load_epidata(\"marburg\") #> Warning in pretty_article_label(articles, mark_multiple): There are 1 articles #> with missing first author surname. #> Warning in pretty_article_label(articles, mark_multiple): There are 1 articles #> with missing first author surname and first author first name. #> Warning in pretty_article_label(articles, mark_multiple): There are 1 articles #> with missing year of publication. #> Data loaded for marburg names(marburg_data) #> [1] \"articles\"  \"params\"    \"models\"    \"outbreaks\" marburg_params <- marburg_data$params delay_dist_rows <- grepl(   pattern = \"Human delay\",   x = marburg_params$parameter_type,   fixed = TRUE ) marburg_params <- marburg_params[delay_dist_rows, ] marburg_params #> # A tibble: 14 × 59 #>    parameter_data_id    article_id parameter_type parameter_value parameter_unit #>    <chr>                     <int> <chr>                    <dbl> <chr>          #>  1 ace3e3fc6f40bef6da4…          6 Human delay -…             4   Days           #>  2 c2a35e68034b7258065…          6 Human delay -…            NA   Days           #>  3 cef9471d52ca35358d7…          6 Human delay -…             9   Days           #>  4 0106582cf5ed3c52d5e…         20 Human delay -…            NA   Days           #>  5 056a8d6b5f9aee3622d…         27 Human delay -…             9   Days           #>  6 ce3976e2e15df3f6fb9…         27 Human delay -…             5.4 Days           #>  7 3bf73665fa67a6ba7f7…         27 Human delay -…             7   Days           #>  8 ba019f18acac9c5b0b7…         27 Human delay -…             9.3 Days           #>  9 71798b4154011dcd008…         27 Human delay -…             9   Days           #> 10 b91f018b5ca72c9293d…         42 Human delay -…             9   Days           #> 11 e95844c29c00b70dee0…         42 Human delay -…             4   Days           #> 12 415a27bceff2afce958…         42 Human delay -…            22   Days           #> 13 7ce1ea4e35a494de06a…         42 Human delay -…            14.3 Days           #> 14 0eb36537ee9159b12d2…         57 Human delay -…             4.5 Days           #> # ℹ 54 more variables: parameter_lower_bound <dbl>, #> #   parameter_upper_bound <dbl>, parameter_value_type <chr>, #> #   parameter_uncertainty_single_value <dbl>, #> #   parameter_uncertainty_singe_type <chr>, #> #   parameter_uncertainty_lower_value <dbl>, #> #   parameter_uncertainty_upper_value <dbl>, parameter_uncertainty_type <chr>, #> #   cfr_ifr_numerator <int>, cfr_ifr_denominator <int>, … marburg_incub <- marburg_params[2, ] marburg_incub #> # A tibble: 1 × 59 #>   parameter_data_id     article_id parameter_type parameter_value parameter_unit #>   <chr>                      <int> <chr>                    <dbl> <chr>          #> 1 c2a35e68034b72580654…          6 Human delay -…              NA Days           #> # ℹ 54 more variables: parameter_lower_bound <dbl>, #> #   parameter_upper_bound <dbl>, parameter_value_type <chr>, #> #   parameter_uncertainty_single_value <dbl>, #> #   parameter_uncertainty_singe_type <chr>, #> #   parameter_uncertainty_lower_value <dbl>, #> #   parameter_uncertainty_upper_value <dbl>, parameter_uncertainty_type <chr>, #> #   cfr_ifr_numerator <int>, cfr_ifr_denominator <int>, … marburg_incub_epidist <- as_epidist(marburg_incub) #> Using Gear (1975). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object marburg_incub_epidist #> Disease: Marburg Virus Disease #> Pathogen: Marburg virus #> Epi Distribution: human delay   incubation period #> Study: Gear (1975). \"<title not available>.\" _<journal not available>_. #> Distribution: NA marburg_incub_epidist$summary_stats #> $mean #> [1] NA #>  #> $mean_ci_limits #> [1] NA NA #>  #> $mean_ci #> [1] NA #>  #> $sd #> [1] NA #>  #> $sd_ci_limits #> [1] NA NA #>  #> $sd_ci #> [1] NA #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] 7 8 marburg_incub_epidist$metadata #> $sample_size #> [1] 1 #>  #> $region #> [1] \"Johannesburg, South Africa\" #>  #> $transmission_mode #> [1] NA #>  #> $vector #> [1] NA #>  #> $extrinsic #> [1] FALSE #>  #> $inference_method #> [1] NA"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"creating-an-epidist-with-full-citation","dir":"Articles","previous_headings":"","what":"Creating an <epidist> with full citation","title":"Using {epireview} with {epiparameter}","text":"last example showed convert epidemiological parameter information, however, may noticed citation created contain information full citation. order provide complete citation <epidist> object, highly recommended know provenance parameters can correctly attribute original authors, need also provide bibliographic information {epireview} well epidemiological parameters. article data needs loaded {epireview} using epireview::load_epidata_raw() rather epireview::load_data() load_data() subsets bibliographic information provide: \"id\", \"first_author_surname\", \"year_publication\", \"article_label\" columns. need match entry epidemiological parameter table citation information article table ensure using correct citation parameter set. Thankfully, can easily achieved {epireview} provides unique IDs table link entries. Now can repeat example converting <epidist> shown , time pass bibliographic information well epidemiological parameter information create full citation. bibliographic information needs passed articles argument. as_epidist() function S3 generic. familiar S3 object-oriented programming R, detail important, however, mean articles argument explicitly function definition as_epidist() (.e. show autocomplete typing function shown read function help page ?as_epidist()). Instead, argument specified part ... argument. articles argument required converting data {epireview} <epidist>, data can converted <epidist> objects require argument.","code":"marburg_incub_epidist$citation #> Gear (1975). \"<title not available>.\" _<journal not available>_. marburg_articles <- load_epidata_raw(   pathogen = \"marburg\",   table = \"article\" ) marburg_articles #> # A tibble: 58 × 25 #>    article_id pathogen   covidence_id first_author_first_n…¹ article_title doi   #>         <dbl> <chr>             <int> <chr>                  <chr>         <chr> #>  1          1 Marburg v…         2059 G A                    Haemorrhagic… NA    #>  2          2 Marburg v…         2042 Christian              Antibodies t… NA    #>  3          3 Marburg v…         1649 Y                      The origin a… 10.1… #>  4          4 Marburg v…         1692 D.H.                   Marburg-Viru… NA    #>  5          5 Marburg v…         2597 E. D.                  Filovirus ac… NA    #>  6          6 Marburg v…         3795 JS                     Outbreak of … 10.1… #>  7          7 Marburg v…         2596 E.D.                   Haemorrhagic… NA    #>  8          8 Marburg v…         1615 O                      Viral hemorr… 10.4… #>  9          9 Marburg v…         1693 Smiley                 Suspected Ex… 10.1… #> 10         10 Marburg v…         1692 D                      Marburg-viru… NA    #> # ℹ 48 more rows #> # ℹ abbreviated name: ¹​first_author_first_name #> # ℹ 19 more variables: journal <chr>, year_publication <int>, volume <int>, #> #   issue <int>, page_first <int>, page_last <int>, paper_copy_only <lgl>, #> #   notes <chr>, first_author_surname <chr>, double_extracted <dbl>, #> #   qa_m1 <int>, qa_m2 <int>, qa_a3 <int>, qa_a4 <int>, qa_d5 <int>, #> #   qa_d6 <int>, qa_d7 <int>, score <dbl>, id <chr> article_row <- match(marburg_incub$id, marburg_articles$id) article_row #> [1] 6 marburg_incub_article <- marburg_articles[article_row, ] marburg_incub_article #> # A tibble: 1 × 25 #>   article_id pathogen    covidence_id first_author_first_n…¹ article_title doi   #>        <dbl> <chr>              <int> <chr>                  <chr>         <chr> #> 1          6 Marburg vi…         3795 JS                     Outbreak of … 10.1… #> # ℹ abbreviated name: ¹​first_author_first_name #> # ℹ 19 more variables: journal <chr>, year_publication <int>, volume <int>, #> #   issue <int>, page_first <int>, page_last <int>, paper_copy_only <lgl>, #> #   notes <chr>, first_author_surname <chr>, double_extracted <dbl>, #> #   qa_m1 <int>, qa_m2 <int>, qa_a3 <int>, qa_a4 <int>, qa_d5 <int>, #> #   qa_d6 <int>, qa_d7 <int>, score <dbl>, id <chr> marburg_incub_epidist <- as_epidist(   marburg_incub,   articles = marburg_incub_article ) #> Using Gear (1975). \"Outbreak of Marburg virus disease in Johannesburg.\" _The #> British Medical Journal_. doi:10.1136/bmj.4.5995.489 #> <https://doi.org/10.1136/bmj.4.5995.489>.  #> To retrieve the citation use the 'get_citation' function #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object marburg_incub_epidist #> Disease: Marburg Virus Disease #> Pathogen: Marburg virus #> Epi Distribution: human delay   incubation period #> Study: Gear (1975). \"Outbreak of Marburg virus disease in Johannesburg.\" _The #> British Medical Journal_. doi:10.1136/bmj.4.5995.489 #> <https://doi.org/10.1136/bmj.4.5995.489>. #> Distribution: NA marburg_incub_epidist$citation #> Gear (1975). \"Outbreak of Marburg virus disease in Johannesburg.\" _The #> British Medical Journal_. doi:10.1136/bmj.4.5995.489 #> <https://doi.org/10.1136/bmj.4.5995.489>."},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"multi-row-epireview-entries","dir":"Articles","previous_headings":"","what":"Multi-row {epireview} entries","title":"Using {epireview} with {epiparameter}","text":"way {epireview} data stored means epidemiological parameter entries require multiple rows. can , example, contain two summary statistics (e.g. mean standard deviation) kept separate rows. order create <epidist> objects contains full information entry multiple rows epidemiological parameters table {epireview} can given as_epidist() create single <epidist> object. can search data entries multiple rows checking duplicated parameter types IDs. Remembering using delay distributions (.e. Human delay) epidemiological parameters, subset . step verified manually ensure entries selected indeed multiple rows reported epidemiological parameter. use first two rows subset table, mean standard deviation generation time Marburg disease. can now convert <epidist>.","code":"multi_row_entries <- duplicated(marburg_params$parameter_type) &   duplicated(marburg_params$id) multi_row_ids <- marburg_params$id[multi_row_entries] multi_row_marburg_params <-   marburg_params[marburg_params$id %in% multi_row_ids, ] marburg_gt <- multi_row_marburg_params[1:2, ] marburg_gt_epidist <- as_epidist(marburg_gt) #> Using Ajelli (2012). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object marburg_gt_epidist #> Disease: Marburg Virus Disease #> Pathogen: Marburg virus #> Epi Distribution: human delay   generation time #> Study: Ajelli (2012). \"<title not available>.\" _<journal not available>_. #> Distribution: NA marburg_gt_epidist$summary_stats #> $mean #> [1] 9 #>  #> $mean_ci_limits #> [1]  8.2 10.0 #>  #> $mean_ci #> [1] 95 #>  #> $sd #> [1] 5.4 #>  #> $sd_ci_limits #> [1] 3.9 8.6 #>  #> $sd_ci #> [1] 95 #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] NA NA"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"entries-with-probability-distributions","dir":"Articles","previous_headings":"","what":"Entries with probability distributions","title":"Using {epireview} with {epiparameter}","text":"example load Ebola epidemiological parameters {epireview} package (entries Marburg parametric distributions). subset data just use epidemiological parameter table, subset table just delay distributions. select 358th entry, serial interval, entry estimated reported Weibull distribution: can now convert <epidist> object. probability distribution serial interval can utilise <epidist> methods. illustrate checking <epidist> parameterised, plotting PDF CDF, generating 10 random numbers sampling distribution.","code":"ebola_data <- load_epidata(\"ebola\") #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata_raw(pathogen, \"outbreak\"): No data found for ebola #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata(\"ebola\"): No outbreaks information found for ebola #> Data loaded for ebola ebola_params <- ebola_data$params delay_dist_rows <- grepl(   pattern = \"Human delay\",   x = ebola_params$parameter_type,   fixed = TRUE ) ebola_params <- ebola_params[delay_dist_rows, ] ebola_params #> # A tibble: 395 × 77 #>    id     parameter_data_id covidence_id pathogen parameter_type parameter_value #>    <chr>  <chr>                    <int> <chr>    <chr>                    <dbl> #>  1 b6168… 6f5cb18602d0dfec…           30 Ebola v… Human delay -…            NA   #>  2 b6168… 55766cedfbf75a9c…           30 Ebola v… Human delay -…            NA   #>  3 0a142… 3ae1f6b55d0f1cc5…           41 Ebola v… Human delay -…             9.2 #>  4 0a142… f0a0191af0663265…           41 Ebola v… Human delay -…             5.8 #>  5 0a142… a83683d0b55750df…           41 Ebola v… Human delay -…            10.6 #>  6 99d84… f4aaae2be84dee6c…           57 Ebola v… Human delay -…             8.6 #>  7 99d84… 1ea610e2489a3257…           57 Ebola v… Human delay -…             4.4 #>  8 99d84… 4316d44cbd32d365…           57 Ebola v… Human delay -…            14.4 #>  9 99d84… 7dfc17eab39f9aa0…           57 Ebola v… Human delay -…             8.6 #> 10 99d84… c9c3fc483d332934…           57 Ebola v… Human delay -…            10.6 #> # ℹ 385 more rows #> # ℹ 71 more variables: exponent <dbl>, parameter_unit <chr>, #> #   parameter_lower_bound <dbl>, parameter_upper_bound <dbl>, #> #   parameter_value_type <chr>, parameter_uncertainty_single_value <dbl>, #> #   parameter_uncertainty_singe_type <chr>, #> #   parameter_uncertainty_lower_value <dbl>, #> #   parameter_uncertainty_upper_value <dbl>, … ebola_si <- ebola_params[358, ] ebola_si #> # A tibble: 1 × 77 #>   id      parameter_data_id covidence_id pathogen parameter_type parameter_value #>   <chr>   <chr>                    <int> <chr>    <chr>                    <dbl> #> 1 b76dcc… 0c3e02f80addfccc…        17730 Ebola v… Human delay -…              12 #> # ℹ 71 more variables: exponent <dbl>, parameter_unit <chr>, #> #   parameter_lower_bound <dbl>, parameter_upper_bound <dbl>, #> #   parameter_value_type <chr>, parameter_uncertainty_single_value <dbl>, #> #   parameter_uncertainty_singe_type <chr>, #> #   parameter_uncertainty_lower_value <dbl>, #> #   parameter_uncertainty_upper_value <dbl>, parameter_uncertainty_type <chr>, #> #   cfr_ifr_numerator <int>, cfr_ifr_denominator <int>, … ebola_si_epidist <- as_epidist(ebola_si) #> Using Marziano (2023). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. ebola_si_epidist #> Disease: Ebola Virus Disease #> Pathogen: Ebola virus #> Epi Distribution: human delay   serial interval #> Study: Marziano (2023). \"<title not available>.\" _<journal not available>_. #> Distribution: weibull #> Parameters: #>   shape: 1.760 #>   scale: 10.140 is_parameterised(ebola_si_epidist) #> [1] TRUE plot(ebola_si_epidist) generate(ebola_si_epidist, times = 10) #>  [1] 17.129838  3.840887  6.913068 14.383495 25.033088  8.693642  8.263781 #>  [8] 11.451308  5.219772  4.697018"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_from_epireview.html","id":"specifying-the-probability-distribution-if-unknown","dir":"Articles","previous_headings":"","what":"Specifying the probability distribution if unknown","title":"Using {epireview} with {epiparameter}","text":"may instances delay distribution reported, either probability distribution fit data, reported probability distribution parameters correspond . cases, parametric probability distribution required particular epidemiological task assuming probability distribution can useful. Please use feature caution. Assuming incorrect probability distribution applying epidemiological method can lead erroneous results. Additionally, probability distribution specified user overwrite probability distribution specified input data (e.g. {epireview} parameter data) can lead error distribution name supplied parameters input incompatible See ?as_epidist details information. Just example load Ebola parameters using epireview::load_epidata() function subset just parameters ($params). use serial interval Ebola reported Faye et al. (2015). stored, two rows parameter table, mean standard deviation, probability distribution specified. code chunk subsets Ebola parameter table just return serial interval Faye et al. (2015). supply data as_epidist() get unparameterised <epidist> object probability distribution stated. Given can convert mean standard deviation parameters probability distribution assume distribution form, can supply data as_epidist(). Ebola serial interval <epidist> can now used various probability distribution methods.","code":"ebola_data <- load_epidata(\"ebola\") #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata_raw(pathogen, \"outbreak\"): No data found for ebola #> Warning: One or more parsing issues, call `problems()` on your data frame for details, #> e.g.: #>   dat <- vroom(...) #>   problems(dat) #> Warning in load_epidata(\"ebola\"): No outbreaks information found for ebola #> Data loaded for ebola ebola_params <- ebola_data$params ebola_si <- ebola_params[   which(     grepl(pattern = \"Faye\", x = ebola_params$article_label, fixed = TRUE) &       grepl(pattern = \"serial\", ebola_params$parameter_type, fixed = TRUE)   ), ] ebola_si_epidist <- as_epidist(ebola_si) #> Using Faye (2015). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object ebola_si_epidist #> Disease: Ebola Virus Disease #> Pathogen: Ebola virus #> Epi Distribution: human delay   serial interval #> Study: Faye (2015). \"<title not available>.\" _<journal not available>_. #> Distribution: NA is_parameterised(ebola_si_epidist) #> [1] FALSE ebola_si_epidist <- as_epidist(ebola_si, prob_dist = \"gamma\") #> Using Faye (2015). \"<title not available>.\" _<journal not available>_.  #> To retrieve the citation use the 'get_citation' function #> Warning: Cannot create full citation for epidemiological parameters without bibliographic information  #>  see ?as_epidist for help. ebola_si_epidist #> Disease: Ebola Virus Disease #> Pathogen: Ebola virus #> Epi Distribution: human delay   serial interval #> Study: Faye (2015). \"<title not available>.\" _<journal not available>_. #> Distribution: gamma #> Parameters: #>   shape: 4.000 #>   scale: 3.550 is_parameterised(ebola_si_epidist) #> [1] TRUE get_parameters(ebola_si_epidist) #> shape scale  #>  4.00  3.55 density(ebola_si_epidist, at = 20) #> [1] 0.03001206 plot(ebola_si_epidist) cdf(ebola_si_epidist, q = 10) #> [1] 0.3118251 plot(ebola_si_epidist, cumulative = TRUE) quantile(ebola_si_epidist, p = 0.5) #> [1] 13.03582 generate(ebola_si_epidist, times = 10) #>  [1] 21.222588  3.271134  7.384133 10.618359 15.691544  7.389448  3.953741 #>  [8] 15.905629  7.924347 12.078103"},{"path":[]},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"about-the-package","dir":"Articles","previous_headings":"","what":"About the package","title":"Data Collation and Synthesis Protocol","text":"{epiparameter} R package contains library epidemiological parameter data functions read handle data. delay distributions describe time two events epidemiology, example incubation period, serial interval onset--death; offspring distributions describe number secondary infections primary infection disease transmission. library compiled process collecting, reviewing extracting data peer-reviewed literature1, including research articles, systematic reviews meta-analyses. epiparameter package act ‘living systematic review’ (sensu Elliott et al. (2014)) actively updated maintained provide reliable source data epidemiological distributions. prevent bias collection assessment data, well-defined methodology searching refining required. document aims provide transparency methodology used epiparameter maintainers outlining steps taken stage data handling. can also serve guide contributors wanting search provide epidemiological parameters currently missing library. protocol also facilitate reproducibility searches, results appraisal steps. large body work methods best conduct literature searches data collection part systematic reviews meta-analyses2, use basis protocol. sources : Cochrane Handbook (Higgins et al. 2022) PRISMA (Page et al. 2021)","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"objective-of-epiparameter","dir":"Articles","previous_headings":"","what":"Objective of {epiparameter}","title":"Data Collation and Synthesis Protocol","text":"defined PRISMA guidelines, clearly stated objective helps refine goal project. epiparameter’s objective provide information collection distributions range infectious diseases accurate, unbiased comprehensive possible. distributions enable outbreak analysts easily access distributions routine analysis. example, delay distributions necessary : calculating case fatality rates adjusting delay outcome, quantifying implications different screening measures quarantine periods, estimating reproduction numbers, scenario modelling using transmission dynamic models.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"contributing-to-the-package","dir":"Articles","previous_headings":"","what":"Contributing to the package","title":"Data Collation and Synthesis Protocol","text":"contribute epiparameter library epidemiological parameter information, added data google sheet. integrated epiparameter library package maintainers, information accessible epiparameter package users.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"scope-of-package","dir":"Articles","previous_headings":"","what":"Scope of package","title":"Data Collation and Synthesis Protocol","text":"epiparameter package spans range infectious diseases, including several distributions disease available. pathogens diseases currently systematically searched included package library : distributions currently included literature search pathogen/disease :","code":"#> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-identifying-distributions-in-the-literature","dir":"Articles","previous_headings":"","what":"Guide to identifying distributions in the literature","title":"Data Collation and Synthesis Protocol","text":"Key word searches: searching literature, use specific search phrases ensure correct literature procured required. use search schema includes searching pathogen disease, desired distribution. search phrase can optionally include specific variant/strain/subtype. search constrained based year publication. Examples searches: “SARS-CoV-2 incubation period” “ebola serial interval” “influenza H7N9 onset admission” However, simple search phrases can return large number irrelevant papers. Using specific search schema depending search engine used. example, using Google Scholar schema like: (“Middle East Respiratory Syndrome” MERS) “onset death” (estimation inference calculation) (ebola EVD) “onset death” (estimation inference calculation) Web Science used: (“Middle East Respiratory Syndrome” MERS) “onset death” estimat* (ebola EVD) “onset death” estimat* refine results suitable set literature. Literature search engines: using selection search engines prevent one source potentially omitting papers. Suggested search sites : Google Scholar, Web Science, PubMed, Scopus. Adding papers: addition database entries papers identified literature search, entries can supplemented recommendations (.e. community) cited paper literature search. Papers may recommended experts research public health communities. plan use two methods community engagement. Firstly open-access Google sheet allows people add distribution data reviewed one epiparameter maintainers incorporated meets quality checks. second method - yet implemented - involves community members uploading data zenodo, can read loaded R using epiparameter checked. Language restrictions: papers English Spanish currently supported epiparameter. Papers written another language verified expert can also included database. However, evaluated review process described result flagged user loaded epiparameter.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-data-refinement-once-sources-identified","dir":"Articles","previous_headings":"","what":"Guide to data refinement once sources identified","title":"Data Collation and Synthesis Protocol","text":"Removing duplicates: library parameters contain duplicates studies, multiple entries per study can included paper reports multiple results (e.g. full data set subset data). Studies use data, subsets supersets data used papers library included. Abstract methods screening: number unique sources identified, reviewed suitability reviewing abstract searching words phrases paper indicate reports parameters summary statistics distribution, can include searching methods section words types distributions (e.g. lognormal), fitting procedures (e.g. maximum likelihood bayesian), searching results parameter estimates. epiparameter library includes entries parameters summary statistics reported distribution specified, entries distribution specified parameters reported. database unsuitable papers kept remind maintainers papers included aids updating database (see ) preventing redundant reviewing previously rejected paper. Stopping criteria: many searches, number results far larger reasonably evaluated outside full systematic review. refining papers contain required information (abstract methods screening), around 10 papers per pathogen screened search (per search round, see updating section details). number papers pass abstract methods screening fewer 10, suitable papers reviewed. Full paper screening: abstract methods screening, papers excluded reviewed full verify indeed contain required information distribution parameters information methodology used. acceptable include secondary source contains information delay distribution primary source unavailable report distribution. inference delay distribution primary subject research article, example inferred used estimation \\(R_0\\) can still included database. Additionally, distribution parameters based illustrative values use simulations - rather inferred data - considered unsuitable excluded. , papers excluded stage recorded database unsuitable sources reasoning prevent reassess updating database. Post hoc removal: epiparameter parameters later identified inappropriate can removed database. cases unlikely limitations can appended onto data entries make users aware limitations (e.g. around assumptions used infer distribution), extreme cases data completely removed database. Note: systematic reviews focusing effect sizes can subject publication bias (e.g. positive significant results literature). However, distribution inference focus significance testing effect sizes, bias considered collection process.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-extracting-parameters","dir":"Articles","previous_headings":"","what":"Guide to extracting parameters","title":"Data Collation and Synthesis Protocol","text":"Extracting parameters: underlying distributions (e.g. gamma, lognormal), parameters (e.g. shape/scale, meanlog/sdlog), summary statistics (e.g. mean, standard deviation, median, range quantiles) given paper, values recorded verbatim paper database. read R using epiparameter package, aspects distribution automatically calculated available. example mean standard deviation gamma distribution reported serial interval values stored database. R, shape scale parameters gamma distribution automatically reconstructed resulting distribution available use. epiparameter library exactly reflects literature. mean information present paper imputed prior knowledge (e.g. vector disease known stated), performing calculating reported values. prevents issue clear provenance data library. requirements entry database defined data dictionary. outline minimal dataset required included epiparameter library : Name disease Type distribution Citation information (author(s) paper, year publication, publication title journal, DOI) Whether distribution extrinsic (e.g. extrinsic incubation period). disease vector-borne NA. Whether distribution fitted discretised, boolean (true false). information database entry non-essential. See data dictionary included epiparameter database fields description range possible values field can take.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"data-quality-assessment-in-epiparameter","dir":"Articles","previous_headings":"","what":"Data quality assessment in {epiparameter}","title":"Data Collation and Synthesis Protocol","text":"inference parameters delay distribution often requires methodological adjustments correct factors otherwise bias estimates. includes accounting interval-censoring data timing event (e.g. exposure pathogen) know certainty, rather within time window. adjusting phase bias distribution estimated growing shrinking stage epidemic. aim epiparameter make judgement parameters ‘better’ others, notify warn user potential limitations data. aspects assessed : 1) whether method includes single double interval-censoring exposure onset times known certainty (.e. single day); 2) method adjust phase bias outbreak ascending descending phase. indicated boolean values indicate whether reported paper users recommended refer back paper determine whether estimates biased.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"guide-to-the-epiparameter-review-process","dir":"Articles","previous_headings":"","what":"Guide to the {epiparameter} review process","title":"Data Collation and Synthesis Protocol","text":"set parameters included database must pass abstract methods screening full screening subsequently review one epiparameter maintainers. process involves running diagnostic checks cross-referencing reported parameters paper ensure match exactly results plot PDF/CDF/PMF matches anything plotted paper, available. prevents possible misinterpretation (e.g. serial interval incubation period). check also includes making sure unique identifiers paper match author’s name, publication year data recorded database.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"updating-parameters-in-the-database","dir":"Articles","previous_headings":"","what":"Updating parameters in the database","title":"Data Collation and Synthesis Protocol","text":"search review stages time consuming continuously carried , aim keep epiparameter library --date living data library conducting regular searches (.e. every 3-4 months) fill missing papers new publication since last search. epidemiological literature can expand rapidly, especially new outbreak. Therefore can optionally include new studies use epidemiological community regular updates. small additions still subject data quality assessment diagnostics ensure accuracy, likely picked subsequent literature searches. likely existing pathogens major increase incidence since last update new papers reporting delay distributions. cases papers previously reviewed due limited reviewing time round updates now checked. particularly value community contributions database, everyone can benefit analysis already conducted, duplicated effort reduced.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/data_protocol.html","id":"database-of-excluded-papers","dir":"Articles","previous_headings":"","what":"Database of excluded papers","title":"Data Collation and Synthesis Protocol","text":"papers returned search results suitable, either stage abstract screening, reviewing entirety paper, recorded database following information: First author’s last name Unique identifier, ideally DOI Journal, pre-print server, host website One several reasons deemed unsuitable Date recording","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"scope","dir":"Articles","previous_headings":"","what":"Scope","title":"Design Principles for {epiparameter}","text":"{epiparameter} R package library epidemiological parameters, provides class (.e. data structure) helper functions working epidemiological parameters distributions. <epidist> class main functional object working epidemiological parameters can hold information delay distributions (e.g. incubation period, serial interval, onset--death distribution) offspring distributions. class number methods, including allowing user easily calculate PDF, CDF, quantile, generate random numbers, calculate distribution mean, plot distribution. <epidist> object can created constructor function epidist(), uncertain whether object <epidist>, can validated validate_epidist(). package also converts distribution parameters summary statistics, vice versa. achieved either conversion extraction methods functions used explained Parameter extraction conversion {epiparameter} vignette.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"output","dir":"Articles","previous_headings":"","what":"Output","title":"Design Principles for {epiparameter}","text":"output epidist() constructor function <epidist> object. list nine elements, element either single type (e.g. character), non-nested list another class. Classes <epidist> elements used existing well developed infrastructure handling certain data types. $prod_dist element uses distribution class – parameterised distribution available – using either <distribution> class {distributional} <distcrete> class {distcrete}. $citation handled using <bibentry> class {utils} package (included part base R recommended packages). functions return simplest type possible, may atomic vector (including single element vectors), un-nested lists.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"design-decisions","dir":"Articles","previous_headings":"","what":"Design decisions","title":"Design Principles for {epiparameter}","text":"conversion functions (convert_*) S3 generic functions methods provided {epiparameter} character <epidist> input. follows design pattern packages, {dplyr}, export key data transformation functions S3 generics allow developers extend conversions data objects. conversion functions designed single function exported user summary statistics parameters, another function exported parameters summary statistics. functions use switch() dispatch internal conversion functions. provides minimal number conversion functions package namespace compared exporting conversion function every distribution. large number entries returned reading epidemiological parameters library using epidist_db() function, can flood console, due default list printing R. reasoning <multi_epidist> object minimal class enable cleaner descriptive printing large list <epidist> objects. print.multi_epidist() prints header metadata number <epidist> objects number diseases epidemiological distributions list. also lists diseases epidemiological parameters returned. footer print() function states number <epidist> objects shown, guides use print(n = ...) parameter_tbl() link online database vignette (database.Rmd). Information header footer considered metadata advice prefixed #. package uses S3 classes S3 dispatch exported functions, switch() .call() dispatching internal functions. easier develop debug internal functions use S3 dispatch avoids ensure S3 methods registered. Examples S3 dispatch exported functions get_parameters() convert_summary_stats_to_params(). Examples internal dispatch using switch() .call() clean_epidist_params() convert_params_to_summary_stats.character(). function naming convention internal functions dot (.) prefix (e.g. .convert_params_lnorm()).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"dependencies","dir":"Articles","previous_headings":"","what":"Dependencies","title":"Design Principles for {epiparameter}","text":"aim restrict number dependencies minimal required set ease maintenance. current hard dependencies : {checkmate} {distributional} {distcrete} {stats} {utils} {stats} {utils} distributed R language viewed lightweight dependencies, already installed user’s machine R. {checkmate} input checking package widely used across Epiverse-TRACE packages. {distributional} {distcrete} used import S3 classes handling working distributions. required {distcrete} can handle discretised distributions. {jsonlite} suggested dependency used read parameter library stored JSON file. However, read internal function instead data available user via sysdata.rda, {jsonlite} required imported dependency.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/design_principles.html","id":"contribute","dir":"Articles","previous_headings":"","what":"Contribute","title":"Design Principles for {epiparameter}","text":"addition package contributing guide, please refer {epiparameter} specific contributing guidelines adding epidemiological parameter package library.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"use-case","dir":"Articles","previous_headings":"","what":"Use case","title":"Getting Started with {epiparameter}","text":"outbreak known potentially novel pathogen detected key parameters delay distributions (e.g. incubation period serial interval) required interpret early data. {epiparameter} can provide distributions selection published sources, past analysis similar pathogen, order provide relevant epidemiological parameters new analysis.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"working-with-epiparameter-data","dir":"Articles","previous_headings":"","what":"Working with {epiparameter} data","title":"Getting Started with {epiparameter}","text":"{epiparameter} introduces two new classes working epidemiological parameters R: <epidist>: Contains name disease, name epidemiological distribution, parameters (available) citation information parameter source, well information. <vb_epidist>: list two <epidist> objects vector-borne disease. One human (intrinsic) distribution, one vector (extrinsic). probability distribution (prob_distribution) argument requires distribution specified standard R naming. cases distribution’s name, e.g., gamma weibull. Examples distribution name R name differ lognormal lnorm, negative binomial nbinom, geometric geom, poisson pois.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"library-of-epidemiological-parameters","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Library of epidemiological parameters","title":"Getting Started with {epiparameter}","text":"First, introduce library, database, epidemiological parameters available {epiparameter}. library stored package JSON file can read R using epidist_db() function. default entries library supplied. output list <epidist> objects, element list corresponds entry parameter database. Technical note: reason object look like regular R list uses custom print method print summary data console 5 entries prevent large list flooding console. number database entries returned less equal 5 print look like standard R list. see full list diseases distributions stored library use parameter_tbl() function. show first six rows output. parameter_tbl() can also subset database supplied function. details data collation library parameters can found Data Collation Synthesis Protocol vignette.","code":"epi_dist_db <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function epi_dist_db #> # List of 122 <epidist> objects #> Number of diseases: 23 #> ❯ Adenovirus ❯ Chikungunya ❯ COVID-19 ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ Marburg Virus Disease ❯ Measles ❯ MERS ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ Rhinovirus ❯ Rift Valley Fever ❯ RSV ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease #> Number of epi distributions: 12 #> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval #> [[1]] #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.247 #>   sdlog: 0.975 #>  #> [[2]] #> Disease: Human Coronavirus #> Pathogen: Human_Cov #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.742 #>   sdlog: 0.918 #>  #> [[3]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.660 #>   sdlog: 1.205 #>  #> # ℹ 119 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html parameter_tbl(multi_epidist = epi_dist_db) #> # Parameter table: #> # A data frame:    122 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 Adenovi… Adenovi… incubation peri… lnorm             Lessl…  2009          14 #>  2 Human C… Human_C… incubation peri… lnorm             Lessl…  2009          13 #>  3 SARS     SARS-Co… incubation peri… lnorm             Lessl…  2009         157 #>  4 Influen… Influen… incubation peri… lnorm             Lessl…  2009         151 #>  5 Influen… Influen… incubation peri… lnorm             Lessl…  2009          90 #>  6 Influen… Influen… incubation peri… lnorm             Lessl…  2009          78 #>  7 Measles  Measles… incubation peri… lnorm             Lessl…  2009          55 #>  8 Parainf… Parainf… incubation peri… lnorm             Lessl…  2009          11 #>  9 RSV      RSV      incubation peri… lnorm             Lessl…  2009          24 #> 10 Rhinovi… Rhinovi… incubation peri… lnorm             Lessl…  2009          28 #> # ℹ 112 more rows parameter_tbl(multi_epidist = epi_dist_db, disease = \"Ebola\") #> # Parameter table: #> # A data frame:    17 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 Ebola V… Ebola V… offspring distr… nbinom            Lloyd…  2005          13 #>  2 Ebola V… Ebola V… incubation peri… lnorm             Eichn…  2011         196 #>  3 Ebola V… Ebola V… onset to death   gamma             The E…  2018          14 #>  4 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015        1798 #>  5 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015          49 #>  6 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015         957 #>  7 Ebola V… Ebola V… incubation peri… gamma             WHO E…  2015         792 #>  8 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015         305 #>  9 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015          37 #> 10 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015         147 #> 11 Ebola V… Ebola V… serial interval  gamma             WHO E…  2015         112 #> 12 Ebola V… Ebola V… hospitalisation… gamma             WHO E…  2015        1167 #> 13 Ebola V… Ebola V… hospitalisation… gamma             WHO E…  2015        1004 #> 14 Ebola V… Ebola V… notification to… gamma             WHO E…  2015        2536 #> 15 Ebola V… Ebola V… notification to… gamma             WHO E…  2015        1324 #> 16 Ebola V… Ebola V… onset to death   gamma             WHO E…  2015        2741 #> 17 Ebola V… Ebola V… onset to discha… gamma             WHO E…  2015        1335"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"single-set-of-epidemiological-parameters","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Single set of epidemiological parameters","title":"Getting Started with {epiparameter}","text":"core data structure introduced {epiparameter} package <epidist> class. holds single set epidemiological parameters. <epidist> object can : Pulled database (epidist_db()) Created manually (using class constructor function: epidist()) arguments specified example using class constructor (epidist()) , example metadata parameter uncertainty (uncertainty) provided. See help documentation epidist() function using ?epidist see argument. Also see documentation <epidist> helper functions, e.g., ?create_epidist_citation(). Manually creating <epidist> objects can especially useful new parameter estimates become available yet incorporated {epiparameter} library. seen examples vignette, <epidist> class custom printing method shows disease, pathogen (known), epidemiological distribution, citation study parameters probability distribution parameter distribution (available).","code":"# <epidist> from database  # fetch <epidist> for COVID-19 incubation period from database # return only a single <epidist> covid_incubation <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function covid_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.525 #>   sdlog: 0.629 # <epidist> using constructor function covid_incubation <- epidist(   disease = \"COVID-19\",   pathogen = \"SARS-CoV-2\",   epi_dist = \"incubation period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 2, scale = 1),   summary_stats = create_epidist_summary_stats(mean = 2),   citation = create_epidist_citation(     author = person(       given = list(\"John\", \"Amy\"),       family = list(\"Smith\", \"Jones\")     ),     year = 2022,     title = \"COVID Incubation Period\",     journal = \"Epi Journal\",     doi = \"10.27861182.x\"   ) ) #> Using Smith J, Jones A (2022). \"COVID Incubation Period.\" _Epi Journal_. #> doi:10.27861182.x <https://doi.org/10.27861182.x>.  #> To retrieve the citation use the 'get_citation' function covid_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Smith J, Jones A (2022). \"COVID Incubation Period.\" _Epi Journal_. #> doi:10.27861182.x <https://doi.org/10.27861182.x>. #> Distribution: gamma #> Parameters: #>   shape: 2.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"benefit-of-epidist","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Benefit of <epidist>","title":"Getting Started with {epiparameter}","text":"providing consistent robust object store epidemiological parameters, <epidist> objects can applied epidemiological pipelines, example {episoap}. data contained within object (e.g. parameter values, pathogen type, etc.) can modified pipeline continue operate class unchanged.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"subsetting-database","dir":"Articles","previous_headings":"","what":"Subsetting database","title":"Getting Started with {epiparameter}","text":"database can subset directly epidist_db(). results can subset author. recommended use family name first author instead full name. first author matched entry source multiple authors. results can subset using subset argument, example subset = sample_size > 100 return entries sample size greater 100. See ?epidist_db() details use argument subset database entries get returned.","code":"epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation period\",   author = \"Linton\" ) #> Returning 3 results that match the criteria (3 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function #> # List of 3 <epidist> objects #> Number of diseases: 1 #> ❯ COVID-19 #> Number of epi distributions: 1 #> ❯ incubation period #> [[1]] #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.456 #>   sdlog: 0.555 #>  #> [[2]] #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.611 #>   sdlog: 0.472 #>  #> [[3]] #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). \"Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.\" _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.525 #>   sdlog: 0.629 #>  #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"adding-library-entries-and-contributing-to-epiparameter","dir":"Articles","previous_headings":"","what":"Adding library entries and contributing to {epiparameter}","title":"Getting Started with {epiparameter}","text":"set epidemiological parameter inferred known user yet incorporated {epiparameter} database, parameters can manually added library. Note adds parameters library environment, save database file package. library epidemiological parameters living database, new studies published hope incorporate . Due large time requirement searching recording parameters database welcome others add parameters either making pull request package adding information contributing spreadsheet. incorporated database package maintainers. See Data Collation Synthesis Protocol vignette information contributing library epidemiological parameters.","code":"# wrap <epidist> in list to append to database new_db <- append(epi_dist_db, list(covid_incubation))"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"distribution-functions","dir":"Articles","previous_headings":"","what":"Distribution functions","title":"Getting Started with {epiparameter}","text":"<epidist> objects store distributions, mathematical functions distribution can easily extracted directly . often useful access probability density function, cumulative distribution function, quantiles distribution, generate random numbers distribution <epidist> object. distribution functions {epiparameter} allow users easily use .","code":"ebola_incubation <- epidist_db(   disease = \"Ebola\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using WHO Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Blake I, #> Brennan R, Cori A, Donnelly C, Dorigatti I, Dye C, Eckmanns T, Ferguson #> N, Formenty P, Fraser C, Garcia E, Garske T, Hinsley W, Holmes D, #> Hugonnet S, Iyengar S, Jombart T, Krishnan R, Meijers S, Mills H, #> Mohamed Y, Nedjati-Gilani G, Newton E, Nouvellet P, Pelletier L, #> Perkins D, Riley S, Sagrado M, Schnitzler J, Schumacher D, Shah A, Van #> Kerkhove M, Varsaneux O, Kannangarage N (2015). \"West African Ebola #> Epidemic after One Year — Slowing but Not Yet under Control.\" _The New #> England Journal of Medicine_. doi:10.1056/NEJMc1414992 #> <https://doi.org/10.1056/NEJMc1414992>..  #> To retrieve the citation use the 'get_citation' function density(ebola_incubation, at = 0.5) #> [1] 0.03608013 cdf(ebola_incubation, q = 0.5) #> [1] 0.01178094 quantile(ebola_incubation, p = 0.5) #> [1] 8.224347 generate(ebola_incubation, times = 10) #>  [1]  0.7464232  1.8696650  6.9982148 13.0108742  2.1266018  5.4595597 #>  [7]  0.4965333  3.7836991  2.4298127  0.3236717"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"plotting-epidemiological-distributions","dir":"Articles","previous_headings":"","what":"Plotting epidemiological distributions","title":"Getting Started with {epiparameter}","text":"<epidist> objects can easily plotted see PDF CDF distribution.  default plotting range time since infection zero 99th quantile distribution. can altered specifying xlim argument plotting <epidist> object.  plotting function can useful visually comparing epidemiological distributions different publications disease. addition, plotting distribution manually creating <epidist> help check parameters sensible produce expected distribution.","code":"plot(ebola_incubation) plot(ebola_incubation, xlim = c(1, 25))"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"conversion","dir":"Articles","previous_headings":"Parameter conversion and extraction","what":"Conversion","title":"Getting Started with {epiparameter}","text":"Parameters often reported literature mean standard deviation (variance). summary statistics can often (analytically) converted parameters distribution using conversion function package (convert_summary_stats_to_params()). also provide conversion functions opposite direction, parameters summary statistics (convert_params_to_summary_stats()).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"extraction","dir":"Articles","previous_headings":"Parameter conversion and extraction","what":"Extraction","title":"Getting Started with {epiparameter}","text":"functions extract_param() handles extraction parameter estimates summary statistics. two extractions currently supported {epiparameter} percentiles median range.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-percentiles","dir":"Articles","previous_headings":"Extraction Bias","what":"Extraction by percentiles","title":"{epiparameter} Extraction Bias Analysis","text":"First explore extraction percentiles. study reports percentiles distribution, usually symmetrical (e.g. 5th 95th, 2.5th 97.5th). However, instances, asymmetrical percentiles available. test whether asymmetry varying degrees influences bias parameter extraction distributions. set parameter space explore: Now can run extraction point parameter space. set seed control stochasticity estimating parameters, however changing removing seed drastically change results interpretation. extract_param() function re-runs optimisation convergence set tolerance achieved (maximum number iterations reached) reliably return global optimum. theory, help minimise bias instability parameter estimation. See function documentation (?extract_param()) Conversion Extraction vignette details. extraction bias can explored:","code":"distributions <- c(\"gamma\", \"lnorm\", \"weibull\") dist_parameters <- seq(0.5, 2, 0.5) lower_percentiles <- c(2.5, 5, 25, 40) upper_percentiles <- c(60, 95, 97.5)  parameters_perc <- expand.grid(   dist = distributions,   param_1 = dist_parameters,   param_2 = dist_parameters,   lower = lower_percentiles,   upper = upper_percentiles )  # calculate the degree of asymmetry for each percentile combination lw_interval_diff <- abs(0 - parameters_perc$lower) up_interval_diff <- abs(100 - parameters_perc$upper) deg_asym <- abs(lw_interval_diff - up_interval_diff)  # add degree of asymmetry to percentiles parameters_perc <- cbind(parameters_perc, deg_asym)  # divide percentiles by 100 to make them probabilities for quantile functions parameters_perc$lower <- parameters_perc$lower / 100 parameters_perc$upper <- parameters_perc$upper / 100 set.seed(1) estim_params <- vector(\"list\", nrow(parameters_perc)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_perc))) {   dist <- as.character(parameters_perc[params_idx, \"dist\"])   percen <- unname(unlist(parameters_perc[params_idx, c(\"lower\", \"upper\")]))    if (dist == \"lnorm\") {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         meanlog = parameters_perc[params_idx, \"param_1\"],         sdlog = parameters_perc[params_idx, \"param_2\"]       )     )   } else {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         shape = parameters_perc[params_idx, \"param_1\"],         scale = parameters_perc[params_idx, \"param_2\"]       )     )   }    # message about stochastic optimisation suppressed   estim_params[[params_idx]] <- suppressMessages(     extract_param(       type = \"percentiles\",       values = true_values,       distribution = dist,       percentiles = percen     )   ) }  # combine results results <- cbind(parameters_perc, do.call(rbind, estim_params))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"lower\", \"upper\",   \"deg_asym\", \"estim_param_1\", \"estim_param_2\" )  # calculate absolute difference between true parameter and estimated value results <- cbind(   results,   diff_param_1 = abs(results$param_1 - results$estim_param_1),   diff_param_2 = abs(results$param_2 - results$estim_param_2) ) # plot differences by distribution ggplot(data = results) +   geom_point(mapping = aes(     x = diff_param_1,     y = diff_param_2,     colour = deg_asym   )) +   scale_x_continuous(name = \"Parameter 1 Difference (|true - estimated|)\") +   scale_y_continuous(name = \"Parameter 2 Difference (|true - estimated|)\") +   labs(colour = \"Percentile Asym.\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   )"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-median-and-range","dir":"Articles","previous_headings":"Extraction Bias","what":"Extraction by median and range","title":"{epiparameter} Extraction Bias Analysis","text":"analysis can repeated, time using summary statistic possibly reported studies: median range data. extraction number samples used infer distribution required can impact possible range exhibited data. Set parameter space: Plot results:","code":"n_samples <- c(10, 50, 100) parameters_range <- expand.grid(   dist = distributions, # same as above   param_1 = dist_parameters, # same as above   param_2 = dist_parameters, # same as above   n_samples = n_samples ) estim_params <- vector(\"list\", nrow(parameters_range)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_range))) {   dist <- as.character(parameters_range[params_idx, \"dist\"])   n_samples <- parameters_range[params_idx, \"n_samples\"]   # while loop to ensure values are min < median < max   resample_values <- TRUE   while (resample_values) {     if (dist == \"lnorm\") {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     } else {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     }     true_values <- c(true_median, true_range)     if (true_values[2] < true_values[1] && true_values[1] < true_values[3]) {       resample_values <- FALSE     }   }   # message about stochastic optimisation suppressed   estim_params[[params_idx]] <- suppressMessages(     expr = extract_param(       type = \"range\",       values = true_values,       distribution = dist,       samples = n_samples     )   ) } #> Warning: Maximum optimisation iterations reached, returning result early.  #> Result may not be reliable. # combine results results <- cbind(parameters_range, do.call(rbind, estim_params))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"n_samples\", \"estim_param_1\", \"estim_param_2\" )  # calculate absolute difference between true parameter and estimated value results <- cbind(   results,   diff_param_1 = abs(results$param_1 - results$estim_param_1),   diff_param_2 = abs(results$param_2 - results$estim_param_2) ) # plot differences by distribution ggplot(data = results) +   geom_point(     mapping = aes(       x = diff_param_1,       y = diff_param_2,       colour = n_samples     )   ) +   scale_x_continuous(name = \"Parameter 1 Difference (|true - estimated|)\") +   scale_y_continuous(name = \"Parameter 2 Difference (|true - estimated|)\") +   labs(colour = \"No. Samples\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   )"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-percentiles-1","dir":"Articles","previous_headings":"Extraction precision","what":"Extraction by percentiles","title":"{epiparameter} Extraction Bias Analysis","text":"two analyses used single extraction (replicate), however, may estimation parameters unstable given set percentiles median range. Therefore, finish test whether repeated extraction parameters single percentile large variance indicate parameter extraction unstable, imprecise, potentially untrustworthy. use parameter space percentiles defined (parameters_perc). Now can run extraction set replicates compute variance parameter estimates replicates.","code":"estim_param_var <- vector(\"list\", nrow(parameters_perc)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_perc))) {   dist <- as.character(parameters_perc[params_idx, \"dist\"])   percen <- unname(unlist(parameters_perc[params_idx, c(\"lower\", \"upper\")]))    if (dist == \"lnorm\") {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         meanlog = parameters_perc[params_idx, \"param_1\"],         sdlog = parameters_perc[params_idx, \"param_2\"]       )     )   } else {     true_values <- do.call(       paste0(\"q\", dist),       list(         p = percen,         shape = parameters_perc[params_idx, \"param_1\"],         scale = parameters_perc[params_idx, \"param_2\"]       )     )   }    # message about stochastic optimisation suppressed   estim <- suppressMessages(     replicate(       n = 5,       expr = extract_param(         type = \"percentiles\",         values = true_values,         distribution = dist,         percentiles = percen       )     )   )   estim_param_var[[params_idx]] <- apply(estim, MARGIN = 1, FUN = var) }  # combine results results <- cbind(parameters_perc, do.call(rbind, estim_param_var))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"lower\", \"upper\",   \"deg_asym\", \"estim_param_1_var\", \"estim_param_2_var\" ) ggplot(data = results) +   geom_point(mapping = aes(     x = estim_param_1_var,     y = estim_param_2_var,     colour = deg_asym   )) +   scale_x_continuous(name = \"Parameter 1 Variance\") +   scale_y_continuous(name = \"Parameter 2 Variance\") +   labs(colour = \"Percentile Asym.\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   )"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract-bias.html","id":"extraction-by-median-and-range-1","dir":"Articles","previous_headings":"Extraction precision","what":"Extraction by median and range","title":"{epiparameter} Extraction Bias Analysis","text":"test estimation precision can performed extraction median range. plots vignette, bias low precision high extracting parameters gamma, lognormal Weibull distributions percentiles distribution median range data set. asymmetry percentiles sample size data noticeably influence bias parameter extraction. However, ensure reliable extract use cases extract_param() function recommend checking output spurious results.","code":"estim_param_var <- vector(\"list\", nrow(parameters_range)) # Loop through parameter space estimating parameters for (params_idx in seq_len(nrow(parameters_range))) {   dist <- as.character(parameters_range[params_idx, \"dist\"])   n_samples <- parameters_range[params_idx, \"n_samples\"]    # while loop to ensure values are min < median < max   resample_values <- TRUE   while (resample_values) {     if (dist == \"lnorm\") {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           meanlog = parameters_range[params_idx, \"param_1\"],           sdlog = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     } else {       true_median <- do.call(         paste0(\"q\", dist),         list(           p = 0.5,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- do.call(         paste0(\"r\", dist),         list(           n = n_samples,           shape = parameters_range[params_idx, \"param_1\"],           scale = parameters_range[params_idx, \"param_2\"]         )       )       true_range <- c(min(true_range), max(true_range))     }     true_values <- c(true_median, true_range)     if (true_values[2] < true_values[1] && true_values[1] < true_values[3]) {       resample_values <- FALSE     }   }   # message about stochastic optimisation suppressed   estim <- suppressMessages(     replicate(       n = 5,       expr = extract_param(         type = \"range\",         values = true_values,         distribution = dist,         samples = n_samples       )     )   )   estim_param_var[[params_idx]] <- apply(estim, MARGIN = 1, FUN = var) } #> Warning: Maximum optimisation iterations reached, returning result early.  #> Result may not be reliable. # combine results results <- cbind(parameters_range, do.call(rbind, estim_param_var))  colnames(results) <- c(   \"dist\", \"param_1\", \"param_2\", \"n_samples\", \"estim_param_1_var\",   \"estim_param_2_var\" ) ggplot(data = results) +   geom_point(mapping = aes(     x = estim_param_1_var,     y = estim_param_2_var,     colour = n_samples   )) +   scale_x_continuous(name = \"Parameter 1 Variance\") +   scale_y_continuous(name = \"Parameter 2 Variance\") +   labs(colour = \"No. Samples\") +   theme_bw() +   scale_color_viridis_c() +   facet_wrap(facets = vars(dist), scales = \"free\") +   theme(     strip.background = element_blank(),     axis.text.x = element_text(angle = 30, vjust = 0.5)   )"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"conversion-versus-extraction","dir":"Articles","previous_headings":"","what":"Conversion versus extraction","title":"Parameter extraction and conversion in {epiparameter}","text":"Use conversion possible extraction avoid possible limitations associated numerical optimisation used extraction function extract_param().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"conversions","dir":"Articles","previous_headings":"","what":"Conversions","title":"Parameter extraction and conversion in {epiparameter}","text":"two conversion functions {epiparameter}: convert_params_to_summary_stats() convert_summary_stats_to_params(). convert_params_to_summary_stats() converts one set statistical distribution parameters common summary statistics, convert_summary_stats_to_params() converts summary statistics set parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"conversion-functions","dir":"Articles","previous_headings":"Conversions","what":"Conversion functions","title":"Parameter extraction and conversion in {epiparameter}","text":"conversion functions generic functions. means different types data can supplied first argument correct operation (method) executed. Currently {epiparameter} provides conversion methods character <epidist>. unclear, see examples conversion functions can work supply either character string <epidist>. conversion functions two arguments. first (x) defines distribution want use second (...) lets put many named parameters summary statistics required. arguments passed ... matched name, therefore need match exactly names expected. See function documentation (?convert_params_to_summary_stats ?convert_summary_stats_to_params names). case <epidist> object supplied, parameters summary statistics required conversion nothing needs given extra arguments (.e. ...). currently supported summary statistic conversions {epiparameter} given distribution.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"using-a-character-string-to-name-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Using a character string to name distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"gamma\", shape = 2.5, scale = 1.5) #> $mean #> [1] 3.75 #>  #> $median #> [1] 1.450487 #>  #> $mode #> [1] 2.25 #>  #> $var #> [1] 5.625 #>  #> $sd #> [1] 2.371708 #>  #> $cv #> [1] 0.6324555 #>  #> $skewness #> [1] 1.264911 #>  #> $ex_kurtosis #> [1] 2.4 convert_summary_stats_to_params(\"gamma\", mean = 2, sd = 2) #> $shape #> [1] 1 #>  #> $scale #> [1] 2 convert_summary_stats_to_params(\"gamma\", mean = 2, var = 2) #> $shape #> [1] 2 #>  #> $scale #> [1] 1 convert_summary_stats_to_params(\"gamma\", mean = 2, cv = 2) #> $shape #> [1] 0.25 #>  #> $scale #> [1] 8"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"using-an-epidist","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Using an <epidist>","title":"Parameter extraction and conversion in {epiparameter}","text":"example parameters provided <epidist> example <epidist> missing parameters supplied ... example summary statistics provided <epidist> example <epidist> missing summary statistics supplied ... usage <epidist> repeated every distribution conversion available {epiparameter}. conversions shown distribution also available using <epidist> object, either parameters summary statistics stored <epidist> supplied via named arguments.","code":"edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 2.5, scale = 1.5) ) #> Citation cannot be created as author, year, journal or title is missing convert_params_to_summary_stats(edist) #> $mean #> [1] 3.75 #>  #> $median #> [1] 1.450487 #>  #> $mode #> [1] 2.25 #>  #> $var #> [1] 5.625 #>  #> $sd #> [1] 2.371708 #>  #> $cv #> [1] 0.6324555 #>  #> $skewness #> [1] 1.264911 #>  #> $ex_kurtosis #> [1] 2.4 edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\" ) #> Citation cannot be created as author, year, journal or title is missing #> No adequate summary statistics available to calculate the parameters of the gamma distribution #> Unparameterised <epidist> object convert_params_to_summary_stats(edist, shape = 2.5, scale = 1.5) #> $mean #> [1] 3.75 #>  #> $median #> [1] 1.450487 #>  #> $mode #> [1] 2.25 #>  #> $var #> [1] 5.625 #>  #> $sd #> [1] 2.371708 #>  #> $cv #> [1] 0.6324555 #>  #> $skewness #> [1] 1.264911 #>  #> $ex_kurtosis #> [1] 2.4 edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\",   summary_stats = create_epidist_summary_stats(mean = 3.75, sd = 2.37) ) #> Citation cannot be created as author, year, journal or title is missing convert_summary_stats_to_params(edist) #> $shape #> [1] 2.503605 #>  #> $scale #> [1] 1.49784 edist <- epidist(   disease = \"<Disease name>\",   pathogen = \"<Pathogen name>\",   epi_dist = \"<Epidemilogical Distribution name>\",   prob_distribution = \"gamma\" ) #> Citation cannot be created as author, year, journal or title is missing #> No adequate summary statistics available to calculate the parameters of the gamma distribution #> Unparameterised <epidist> object convert_summary_stats_to_params(edist, mean = 3.75, sd = 2.37) #> $shape #> [1] 2.503605 #>  #> $scale #> [1] 1.49784"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"lognormal-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Lognormal distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"lnorm\", meanlog = 2.5, sdlog = 1.5) #> $mean #> [1] 37.52472 #>  #> $median #> [1] 12.18249 #>  #> $mode #> [1] 1.284025 #>  #> $var #> [1] 11951.62 #>  #> $sd #> [1] 109.3235 #>  #> $cv #> [1] 2.913372 #>  #> $skewness #> [1] 33.46805 #>  #> $ex_kurtosis #> [1] 10075.25 convert_summary_stats_to_params(\"lnorm\", mean = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #>  #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(\"lnorm\", mean = 2, var = 2) #> $meanlog #> [1] 0.4904146 #>  #> $sdlog #> [1] 0.6367614 convert_summary_stats_to_params(\"lnorm\", mean = 2, cv = 2) #> $meanlog #> [1] -0.1115718 #>  #> $sdlog #> [1] 1.268636 convert_summary_stats_to_params(\"lnorm\", median = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #>  #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(\"lnorm\", median = 2, var = 2) #> $meanlog #> [1] 0.4904146 #>  #> $sdlog #> [1] 0.6367614"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"weibull-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Weibull distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"weibull\", shape = 2.5, scale = 1.5) #> $mean #> [1] 1.330896 #>  #> $median #> [1] 1.295452 #>  #> $mode #> [1] 1.22279 #>  #> $var #> [1] 0.3243301 #>  #> $sd #> [1] 0.5694998 #>  #> $cv #> [1] 0.4279072 #>  #> $skewness #> [1] 0.3586318 #>  #> $ex_kurtosis #> [1] -0.1432169 convert_summary_stats_to_params(\"weibull\", mean = 2, sd = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 1.000016 #>  #> $scale #> [1] 2.000014 convert_summary_stats_to_params(\"weibull\", mean = 2, var = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 1.435521 #>  #> $scale #> [1] 2.202641 convert_summary_stats_to_params(\"weibull\", mean = 2, cv = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 0.5427068 #>  #> $scale #> [1] 1.150547"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"negative-binomial-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Negative binomial distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"nbinom\", prob = 0.5, dispersion = 0.5) #> $mean #> [1] 0.5 #>  #> $median #> [1] 0 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 1 #>  #> $sd #> [1] 1 #>  #> $cv #> [1] 2 #>  #> $skewness #> [1] 3 #>  #> $ex_kurtosis #> [1] 12.25 convert_summary_stats_to_params(\"nbinom\", mean = 1, sd = 1) #> $prob #> [1] 1 #>  #> $dispersion #> [1] Inf convert_summary_stats_to_params(\"nbinom\", mean = 1, var = 1) #> $prob #> [1] 1 #>  #> $dispersion #> [1] Inf convert_summary_stats_to_params(\"nbinom\", mean = 1, cv = 1) #> $prob #> [1] 1 #>  #> $dispersion #> [1] Inf"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"geometric-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Geometric distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats(\"geom\", prob = 0.5) #> $mean #> [1] 1 #>  #> $median #> [1] 0 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 2 #>  #> $sd #> [1] 1.414214 #>  #> $cv #> [1] 1.414214 #>  #> $skewness #> [1] 2.12132 #>  #> $ex_kurtosis #> [1] 6.5 convert_summary_stats_to_params(\"geom\", mean = 1) #> $prob #> [1] 0.5"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"extraction","dir":"Articles","previous_headings":"","what":"Extraction","title":"Parameter extraction and conversion in {epiparameter}","text":"two methods extraction implemented {epiparameter}. One estimate parameters given values two percentiles, estimate parameters given median range data. extractions implemented extract_param() function. demonstrate extraction using percentiles. type \"percentiles\", values values reported percentiles, given vector. percentiles, given 0 1, specified vector percentiles. example uses values 1 10 2.5th 97.5th percentile, respectively. example estimate parameters gamma distribution, extraction also implemented lognormal, normal Weibull distributions, specifying \"lnorm\", \"norm\" \"weibull\". message shown running extract_param() make user aware estimates completely reliable due use numerical optimisation. Rerunning function finding parameters returned indicates successfully converged. issue mostly overcome internal setup extract_param() function searches convergence consistent parameter estimates returning user. alternative extraction, median range, can achieved specifying type = \"range\" using samples argument instead percentiles argument. using type = \"percentiles\" samples argument ignored using type = \"range\" percentiles argument ignored. section mentioned extract_param() internal mechanism check parameters consistently converged estimates several optimisation iterations. tolerance convergence number times optimisation can repeated specified control argument extract_param(). set default (tolerance = 1e-5 max_iter = 1000), thus need specified user (shown examples). case maximum number optimisation iterations reached, calculation terminates returning recent optimisation result user along warning message. reasoning default maximum number iterations limit computation time prevent function cycling optimisation routines without converging consistent answer. runtime important parameter accuracy paramount maximum number iterations can increased tolerance decreased. control settings work identically extracting percentiles median range. Donnelly et al. (2003) provides mean variance gamma distribution incubation period SARS. conversion can achieved using general conversion function (convert_summary_stats_to_params()).","code":"extract_param(   type = \"percentiles\",   values = c(1, 10),   distribution = \"gamma\",   percentiles = c(0.025, 0.975) ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>    shape    scale  #> 3.358210 1.284184 extract_param(   type = \"range\",   values = c(10, 5, 15),   distribution = \"lnorm\",   samples = 25 ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>  meanlog    sdlog  #> 2.302584 3.939920 # set seed to ensure warning is produced set.seed(1)  # lower maximum iteration to show warning extract_param(   type = \"range\",   values = c(10, 1, 25),   distribution = \"lnorm\",   samples = 100,   control = list(max_iter = 100) ) #> Warning: Maximum optimisation iterations reached, returning result early.  #> Result may not be reliable. #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>   meanlog     sdlog  #> 2.3025851 0.7942061 # SARS gamma mean and var to shape and scale convert_summary_stats_to_params(\"gamma\", mean = 6.37, var = 16.7) #> $shape #> [1] 2.429754 #>  #> $scale #> [1] 2.621664"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"use-cases","dir":"Articles","previous_headings":"Extraction","what":"Use cases","title":"Parameter extraction and conversion in {epiparameter}","text":"present examples published epidemiological parameters distributions functions outlined can applied get parameters distribution. 75th percentiles reported lognormal distribution Nolen et al. (2016) incubation period mpox (monkeypox). median range provided Thornhill et al. (2022) mpox, want calculate parameters lognormal distribution.","code":"# Mpox lnorm from 75th percentiles in WHO data extract_param(   type = \"percentiles\",   values = c(6, 13),   distribution = \"lnorm\",   percentiles = c(0.125, 0.875) ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>   meanlog     sdlog  #> 2.1783544 0.3360684 # Mpox lnorm from median and range in 2022: extract_param(   type = \"range\",   values = c(7, 3, 20),   distribution = \"lnorm\",   samples = 23 ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>  meanlog    sdlog  #> 1.945910 4.735285"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"assuming-distributions","dir":"Articles","previous_headings":"Extraction","what":"Assuming distributions","title":"Parameter extraction and conversion in {epiparameter}","text":"can case study report summary statistics unspecified distribution just raw data. cases parameterised distribution required downstream analysis functional, parametric, form may assumed. distribution delay distribution (.e. serial interval incubation period) can often sensible assume right-skewed distribution : gamma, lognormal Weibull distributions. also commonly fit distributions epidemiological analysis delay distributions. However, one take care assuming distribution may drastically influence interpretation application epidemiological parameters.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Joshua W. Lambert. Author, maintainer, copyright holder. Adam Kucharski. Author, copyright holder. Carmen Tamayo. Author. Hugo Gruson. Contributor, reviewer. Sebastian Funk. Contributor. Pratik Gupte. Reviewer.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Lambert J, Kucharski , Tamayo C (2024). epiparameter: Library Epidemiological Parameters Helper Functions Classes. doi:10.5281/zenodo.11110881, https://github.com/epiverse-trace/epiparameter/,https://epiverse-trace.github.io/epiparameter/.","code":"@Manual{,   title = {epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes},   author = {Joshua W. Lambert and Adam Kucharski and Carmen Tamayo},   year = {2024},   doi = {10.5281/zenodo.11110881},   url = {https://github.com/epiverse-trace/epiparameter/, https://epiverse-trace.github.io/epiparameter/}, }"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"epiparameter-","dir":"","previous_headings":"","what":"Library of Epidemiological Parameters with Helper Functions and Classes","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"epiparameter R package contains library epidemiological parameters infectious diseases set classes helper functions able work data. also includes functions extract convert parameters reported summary statistics. epiparameter developed Centre Mathematical Modelling Infectious Diseases London School Hygiene Tropical Medicine part Epiverse-TRACE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"easiest way install development version epiparameter use pak package: Alternatively, install pre-compiled binaries Epiverse TRACE R-universe","code":"# check whether {pak} is installed if(!require(\"pak\")) install.packages(\"pak\") pak::pak(\"epiverse-trace/epiparameter\") install.packages(\"epiparameter\", repos = c(\"https://epiverse-trace.r-universe.dev\", \"https://cloud.r-project.org\"))"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"quick-start","dir":"","previous_headings":"","what":"Quick start","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"load library epidemiological parameters R: results list database entries. entry library <epidist> object. results can filtered disease epidemiological distribution. set single_epidist = TRUE want single database entry returned, default (single_epidist = FALSE) return database entries match disease (disease) epidemiological distribution (epi_dist). quickly view list epidemiological distributions returned epidist_db() table, parameter_tbl() gives summary data, offers ability subset data disease, pathogen epidemiological distribution (epi_dist). <epidist> object can plotted.  CDF can also plotted setting cumulative = TRUE.","code":"library(epiparameter) epidists <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function epidists #> # List of 122 <epidist> objects #> Number of diseases: 23 #> ❯ Adenovirus ❯ Chikungunya ❯ COVID-19 ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ Marburg Virus Disease ❯ Measles ❯ MERS ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ Rhinovirus ❯ Rift Valley Fever ❯ RSV ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease #> Number of epi distributions: 12 #> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval #> [[1]] #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.247 #>   sdlog: 0.975 #>  #> [[2]] #> Disease: Human Coronavirus #> Pathogen: Human_Cov #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.742 #>   sdlog: 0.918 #>  #> [[3]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> \"Incubation periods of acute respiratory viral infections: a systematic #> review.\" _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.660 #>   sdlog: 1.205 #>  #> # ℹ 119 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html influenza_incubation <- epidist_db(   disease = \"influenza\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using Virlogeux V, Li M, Tsang T, Feng L, Fang V, Jiang H, Wu P, Zheng J, Lau #> E, Cao Y, Qin Y, Liao Q, Yu H, Cowling B (2015). \"Estimating the #> Distribution of the Incubation Periods of Human Avian Influenza A(H7N9) #> Virus Infections.\" _American Journal of Epidemiology_. #> doi:10.1093/aje/kwv115 <https://doi.org/10.1093/aje/kwv115>..  #> To retrieve the citation use the 'get_citation' function influenza_incubation #> Disease: Influenza #> Pathogen: Influenza-A-H7N9 #> Epi Distribution: incubation period #> Study: Virlogeux V, Li M, Tsang T, Feng L, Fang V, Jiang H, Wu P, Zheng J, Lau #> E, Cao Y, Qin Y, Liao Q, Yu H, Cowling B (2015). \"Estimating the #> Distribution of the Incubation Periods of Human Avian Influenza A(H7N9) #> Virus Infections.\" _American Journal of Epidemiology_. #> doi:10.1093/aje/kwv115 <https://doi.org/10.1093/aje/kwv115>. #> Distribution: weibull #> Parameters: #>   shape: 2.101 #>   scale: 3.839 parameter_tbl(epidists) #> # Parameter table: #> # A data frame:    122 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 Adenovi… Adenovi… incubation peri… lnorm             Lessl…  2009          14 #>  2 Human C… Human_C… incubation peri… lnorm             Lessl…  2009          13 #>  3 SARS     SARS-Co… incubation peri… lnorm             Lessl…  2009         157 #>  4 Influen… Influen… incubation peri… lnorm             Lessl…  2009         151 #>  5 Influen… Influen… incubation peri… lnorm             Lessl…  2009          90 #>  6 Influen… Influen… incubation peri… lnorm             Lessl…  2009          78 #>  7 Measles  Measles… incubation peri… lnorm             Lessl…  2009          55 #>  8 Parainf… Parainf… incubation peri… lnorm             Lessl…  2009          11 #>  9 RSV      RSV      incubation peri… lnorm             Lessl…  2009          24 #> 10 Rhinovi… Rhinovi… incubation peri… lnorm             Lessl…  2009          28 #> # ℹ 112 more rows parameter_tbl(   epidists,   epi_dist = \"onset to hospitalisation\" ) #> # Parameter table: #> # A data frame:    5 × 7 #>   disease  pathogen  epi_distribution prob_distribution author  year sample_size #>   <chr>    <chr>     <chr>            <chr>             <chr>  <dbl>       <dbl> #> 1 MERS     MERS-Cov  onset to hospit… <NA>              Assir…  2013          23 #> 2 COVID-19 SARS-CoV… onset to hospit… gamma             Linto…  2020         155 #> 3 COVID-19 SARS-CoV… onset to hospit… gamma             Linto…  2020          34 #> 4 COVID-19 SARS-CoV… onset to hospit… lnorm             Linto…  2020         155 #> 5 COVID-19 SARS-CoV… onset to hospit… lnorm             Linto…  2020          34 plot(influenza_incubation) plot(influenza_incubation, cumulative = TRUE)"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"parameter-conversion-and-extraction","dir":"","previous_headings":"Quick start","what":"Parameter conversion and extraction","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"parameters distribution can converted mean standard deviation. epiparameter implement variety distributions: gamma lognormal Weibull negative binomial geometric parameters probability distribution can also extracted summary statistics, example, percentiles distribution, median range data. can done : gamma lognormal Weibull normal","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"contributing-to-library-of-epidemiological-parameters","dir":"","previous_headings":"","what":"Contributing to library of epidemiological parameters","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"like contribute different epidemiological parameters stored epiparameter package, can add data public google sheet. spreadsheet contains two example entries guide fields can accept. monitoring sheet new entries subsequently included package. Alternatively, parameters can added JSON file holding data base directly via Pull Request. can find explanation accepted entries column data dictionary.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"help","dir":"","previous_headings":"","what":"Help","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"report bug please open issue","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"contribute","dir":"","previous_headings":"","what":"Contribute","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"Contributions epiparameter welcomed. package contributing guide.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"Please note epiparameter project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"citing-this-package","dir":"","previous_headings":"","what":"Citing this package","title":"Library of Epidemiological Parameters with Helper Functions and Classes","text":"","code":"citation(\"epiparameter\") #> To cite package 'epiparameter' in publications use: #>  #>   Lambert J, Kucharski A, Tamayo C (2024). _epiparameter: Library of #>   Epidemiological Parameters with Helper Functions and Classes_. #>   doi:10.5281/zenodo.11110881 #>   <https://doi.org/10.5281/zenodo.11110881>, #>   <https://github.com/epiverse-trace/epiparameter/,https://epiverse-trace.github.io/epiparameter/>. #>  #> A BibTeX entry for LaTeX users is #>  #>   @Manual{, #>     title = {epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes}, #>     author = {Joshua W. Lambert and Adam Kucharski and Carmen Tamayo}, #>     year = {2024}, #>     doi = {10.5281/zenodo.11110881}, #>     url = {https://github.com/epiverse-trace/epiparameter/, #> https://epiverse-trace.github.io/epiparameter/}, #>   }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.data.frame() method for <epidist> class — as.data.frame.epidist","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":".data.frame() method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"","code":"# S3 method for epidist as.data.frame(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"<data.frame> single row.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"as.data.frame() method for <epidist> class — as.data.frame.epidist","text":"<data.frame> returned contain atomic columns (.e. one object per row), columns lists (.e. multiple objects per row). list columns can contain lists S3 objects (e.g. <bibentry> object citation column).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":".data.frame() method <multi_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"","code":"# S3 method for multi_epidist as.data.frame(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"x <multi_epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"<data.frame> many rows length input list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.data.frame.multi_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"as.data.frame() method for <multi_epidist> class — as.data.frame.multi_epidist","text":"<data.frame> returned contain atomic columns (.e. one object per row), columns lists (.e. multiple objects per row). list columns can contain lists S3 objects (e.g. <bibentry> object citation column).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.function() method for <epidist> class — as.function.epidist","title":"as.function() method for <epidist> class — as.function.epidist","text":"Converts <epidist> object distribution function (see epidist_distribution_functions), either probability density/mass function, (density), cumulative distribution function (cdf), random number generator (generate), quantile (quantile).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"as.function() method for <epidist> class — as.function.epidist","text":"","code":"# S3 method for epidist as.function(x, func_type = c(\"density\", \"cdf\", \"generate\", \"quantile\"), ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"as.function() method for <epidist> class — as.function.epidist","text":"x <epidist> object. func_type single character string specifying distribution convert <epidist> object . Default \"density\". options \"cdf\", \"generate\", \"quantile\". ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"as.function() method for <epidist> class — as.function.epidist","text":"function object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"as.function() method for <epidist> class — as.function.epidist","text":"function returned takes single required argument x.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"Convert tabular information <data.frame> <epidist>. information <data.frame> converted <epidist> function error.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"","code":"# S3 method for data.frame as_epidist(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"x <data.frame>. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.data.frame.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert <data.frame> to an <epidist> object — as_epidist.data.frame","text":"<epidist> object list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert to an <epidist> object — as_epidist","title":"Convert to an <epidist> object — as_epidist","text":"Convert R object <epidist> object. conversion possible function error.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert to an <epidist> object — as_epidist","text":"","code":"as_epidist(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert to an <epidist> object — as_epidist","text":"x object used select method. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert to an <epidist> object — as_epidist","text":"<epidist> object list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert to an <epidist> object — as_epidist","text":"create full citation information article table epireview package corresponding entry need passed function via ... argument. argument called article, matched name $. specify probability distribution pass character string function via ... argument. argument called prob_dist. example, specify gamma distribution: as_epidist(x, prob_dist = \"gamma\"). Warning: distributions specified via prob_dist argument overwrite probability distribution specified x argument. example, probability distribution given epireview entry prob_dist argument specified function may error return unparameterised <epidist> parameterisation becomes incompatible. Valid probability distributions : \"gamma\", \"lnorm\", \"weibull\", \"nbinom\", \"geom\", \"pois\", \"norm\", \"exp\".","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"function can used cases data fitted distribution openly available summary statistics distribution reported data scraped plot quantiles needed order use extract_param() function.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"","code":"calc_disc_dist_quantile(prob, days, quantile)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"prob numeric vector probabilities. days numeric vector days. quantile single numeric vector numerics specifying quantiles extract distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"named vector quantiles.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the quantiles of a probability distribution based on the vector of probabilities and time data (e.g. time since infection) — calc_disc_dist_quantile","text":"","code":"prob <- dgamma(seq(0, 10, length.out = 21), shape = 2, scale = 2) days <- seq(0, 10, 0.5) quantiles <- c(0.025, 0.975) calc_disc_dist_quantile(prob = prob, days = days, quantile = quantiles) #> 0.025 0.975  #>     0     9"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"parameters probability distribution provided (e.g. describing distribution literature) instead summary statistics distribution provided, parameters can usually calculated summary statistics. function can provide convenient wrapper around convert_summary_stats_to_params() extract_param() known summary statistics can used calculate parameters distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"","code":"calc_dist_params(prob_dist, prob_dist_params, summary_stats, sample_size)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters. summary_stats list summary statistics, use create_epidist_summary_stats() create list. list can include summary statistics inferred distribution mean standard deviation, quantiles distribution, information data used fit distribution lower upper range. summary statistics can also include uncertainty around metrics confidence interval around mean standard deviation. sample_size sample size data. needed falling back using median-range extraction calculation.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/calc_dist_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the parameters of a probability distribution from a list of summary statistics — calc_dist_params","text":"hierarchy methods : Conversion prioritised mean standard deviation available mostly analytical conversions (except one Weibull conversions). Next method possible extraction percentiles. method requires lower percentile ((0-50]) upper percentile ((50-100)). multiple percentiles ranges provided lowest value used calculation. last method extraction using median range data.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"function try prevent optimisation local optimum thus checks whether multiple optimisation routines consistently finding parameter values within set tolerance.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"","code":"check_optim_conv(optim_params_list, optim_params, tolerance)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"optim_params_list list, element output stats::optim(). See ?optim details. optim_params list given output stats::optim(). tolerance numeric specifying within disparity convergence parameter estimates function minimisation accepted.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether the optimisation of distribution parameters has converged to stable value for the parameters and function output for multiple iterations — check_optim_conv","text":"Boolean","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"Convert parameters range distributions number summary statistics. summary statistics calculated analytically given parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"","code":"convert_params_to_summary_stats(x, ...)  # S3 method for character convert_params_to_summary_stats(   x = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"),   ... )  # S3 method for epidist convert_params_to_summary_stats(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"x R object. ... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"distribution names parameter names follow style distributions R, example lognormal distribution lnorm, parameters meanlog sdlog.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_to_summary_stats.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert the parameter(s) of a distribution to summary statistics — convert_params_to_summary_stats","text":"","code":"# example using characters convert_params_to_summary_stats(\"lnorm\", meanlog = 1, sdlog = 2) #> $mean #> [1] 20.08554 #>  #> $median #> [1] 2.718282 #>  #> $mode #> [1] 0.04978707 #>  #> $var #> [1] 21623.04 #>  #> $sd #> [1] 147.0477 #>  #> $cv #> [1] 7.321076 #>  #> $skewness #> [1] 414.3593 #>  #> $ex_kurtosis #> [1] 9220557 #>  convert_params_to_summary_stats(\"gamma\", shape = 1, scale = 1) #> $mean #> [1] 1 #>  #> $median #> [1] 0.6931472 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 1 #>  #> $sd #> [1] 1 #>  #> $cv #> [1] 1 #>  #> $skewness #> [1] 2 #>  #> $ex_kurtosis #> [1] 6 #>  convert_params_to_summary_stats(\"nbinom\", prob = 0.5, dispersion = 2) #> $mean #> [1] 2 #>  #> $median #> [1] 1 #>  #> $mode #> [1] 1 #>  #> $var #> [1] 4 #>  #> $sd #> [1] 2 #>  #> $cv #> [1] 1 #>  #> $skewness #> [1] 1.5 #>  #> $ex_kurtosis #> [1] 4 #>   # example using <epidist> epidist <- epidist_db(single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function convert_params_to_summary_stats(epidist) #> $mean #> [1] 9.7 #>  #> $median #> [1] 2.576957 #>  #> $mode #> [1] 0.1818772 #>  #> $var #> [1] 1239.04 #>  #> $sd #> [1] 35.2 #>  #> $cv #> [1] 3.628866 #>  #> $skewness #> [1] 58.67393 #>  #> $ex_kurtosis #> [1] 46586.04 #>   # example using <epidist> and specifying parameters epidist <- epidist_db(   disease = \"Influenza\",   author = \"Virlogeux\",   subset = prob_dist == \"weibull\" ) #> Returning 4 results that match the criteria (3 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function convert_params_to_summary_stats(epidist[[2]], shape = 1, scale = 1) #> $mean #> [1] 1 #>  #> $median #> [1] 0.6931472 #>  #> $mode #> [1] 0 #>  #> $var #> [1] 1 #>  #> $sd #> [1] 1 #>  #> $cv #> [1] 1 #>  #> $skewness #> [1] 2 #>  #> $ex_kurtosis #> [1] 6 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"Convert summary statistics range distributions distribution's parameters. summary statistics calculated analytically given parameters. exception Weibull distribution uses root finding numerical method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"","code":"convert_summary_stats_to_params(x, ...)  # S3 method for character convert_summary_stats_to_params(   x = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"),   ... )  # S3 method for epidist convert_summary_stats_to_params(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"x R object. ... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"list either one two elements (depending many parameters distribution ).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"Summary statistics named accordingly (case-sensitive): mean: mean median: median mode: mode variance: var standard deviation: sd coefficient variation: cv skewness: skewness excess kurtosis: ex_kurtosis Note: combinations summary statistics can converted distribution parameters. case function error stating parameters calculated given input. distribution names parameter names follow style distributions R, example lognormal distribution lnorm, parameters meanlog sdlog.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_to_params.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert the summary statistics of a distribution to parameters — convert_summary_stats_to_params","text":"","code":"# examples using characters convert_summary_stats_to_params(\"lnorm\", mean = 1, sd = 1) #> $meanlog #> [1] -0.3465736 #>  #> $sdlog #> [1] 0.8325546 #>  convert_summary_stats_to_params(\"weibull\", mean = 2, var = 2) #> Numerical approximation used, results may be unreliable. #> $shape #> [1] 1.435521 #>  #> $scale #> [1] 2.202641 #>  convert_summary_stats_to_params(\"geom\", mean = 2) #> $prob #> [1] 0.3333333 #>   # examples using <epidist> epidist <- epidist_db(single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function convert_summary_stats_to_params(epidist) #> $meanlog #> [1] 0.9466094 #>  #> $sdlog #> [1] 1.628199 #>   # example using <epidist> and specifying summary stats epidist$summary_stats <- list() convert_summary_stats_to_params(epidist, mean = 10, sd = 2) #> $meanlog #> [1] 2.282975 #>  #> $sdlog #> [1] 0.1980422 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a citation for an <epidist> object — create_epidist_citation","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"helper function creating <epidist> object create citation list sensible defaults, type checking arguments help remember citation information accepted list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"","code":"create_epidist_citation(   author = utils::person(),   year = NA_integer_,   title = NA_character_,   journal = NA_character_,   doi = NA_character_,   pmid = NA_integer_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"author Either <person>, character string, vector list characters case multiple authors. Specify full name (\"<given name>\" \"<family name>\"). using characters make sure name can converted <person> (see .person()). Use white space separation names. Multiple names can stored within single <person> (see person()). year numeric year publication. title character string title article published epidemiological parameters. journal character string name journal published article published epidemiological parameters. can also pre-print server, e.g., medRxiv. doi character string Digital Object Identifier (DOI) assigned papers unique paper. pmid character string PubMed unique identifier number (PMID) assigned papers give unique identifier within PubMed.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"<bibentry> object citation","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"function acts wrapper around bibentry() create citations sources reporting epidemiological parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_citation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a citation for an <epidist> object — create_epidist_citation","text":"","code":"create_epidist_citation(   author = person(given = \"John\", family = \"Smith\"),   year = 2002,   title = \"COVID-19 incubation period\",   journal = \"Epi Journal\",   doi = \"10.19832/j.1366-9516.2012.09147.x\" ) #> Using Smith J (2002). “COVID-19 incubation period.” _Epi Journal_. #> doi:10.19832/j.1366-9516.2012.09147.x #> <https://doi.org/10.19832/j.1366-9516.2012.09147.x>.  #> To retrieve the citation use the 'get_citation' function #> Smith J (2002). “COVID-19 incubation period.” _Epi Journal_. #> doi:10.19832/j.1366-9516.2012.09147.x #> <https://doi.org/10.19832/j.1366-9516.2012.09147.x>."},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify metadata associated with data set — create_epidist_metadata","title":"Specify metadata associated with data set — create_epidist_metadata","text":"helper function creating <epidist> object create metadata list sensible defaults, type checking arguments help remember metadata list structure (element names).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify metadata associated with data set — create_epidist_metadata","text":"","code":"create_epidist_metadata(   sample_size = NA_integer_,   region = NA_character_,   transmission_mode = NA_character_,   vector = NA_character_,   extrinsic = FALSE,   inference_method = NA_character_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify metadata associated with data set — create_epidist_metadata","text":"sample_size sample data used fit delay distribution. usually number people data primary possibly secondary event interest. cases sample size stated NA can used. region geographical location data collected. can either given sub-national, national, continental. Multiple nested regions can given comma separated. region specified NA can given. transmission_mode character string specifying pathogen transmitted. information used determine whether epidemiological parameters vector-borne disease (.e. transmitted humans intermediate vector), specified transmission_mode = \"vector_borne\". vector name vector transmitting vector-borne disease. can common name, latin binomial name specific vector species. common name taxonomic name can given one given parentheses. disease vector-borne NA given. extrinsic boolean value defining whether data entry extrinsic delay distribution, extrinsic incubation period. field required intrinsic extrinsic delay distributions stored separate entries database can linked. disease vector-borne FALSE given. See Details explanation extrinsic distribution. inference_method type inference used fit delay distribution data. Abbreviations model fitting techniques can specified long non-ambiguous. field used determine whether uncertainty intervals possibly specified fields : confidence intervals (case maximum likelihood), credible intervals (case bayesian inference). Uncertainty bounds another types inference methods, inference method unstated assumed confidence intervals. inference method unknown disease probability distribution NA can given.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify metadata associated with data set — create_epidist_metadata","text":"named list containing information sample size study, geography, whether disease vector-borne whether intrinsic extrinsic distribution well method distribution parameter estimation.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Specify metadata associated with data set — create_epidist_metadata","text":"vector-borne diseases transmissibility disease dependent time taken host (.e. human) become infectious, also time takes vector become infectious. Therefore, extrinsic delay, vector infected yet infectious can role spread disease.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_metadata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify metadata associated with data set — create_epidist_metadata","text":"","code":"# it will automatically populate the fields with defaults if left empty create_epidist_metadata() #> $sample_size #> [1] NA #>  #> $region #> [1] NA #>  #> $transmission_mode #> [1] NA #>  #> $vector #> [1] NA #>  #> $extrinsic #> [1] FALSE #>  #> $inference_method #> [1] NA #>   # supplying each field create_epidist_metadata(   sample_size = 10,   region = \"UK\",   transmission_mode = \"vector_borne\",   vector = \"mosquito\",   extrinsic = FALSE,   inference_method = \"MLE\" ) #> $sample_size #> [1] 10 #>  #> $region #> [1] \"UK\" #>  #> $transmission_mode #> [1] \"vector_borne\" #>  #> $vector #> [1] \"mosquito\" #>  #> $extrinsic #> [1] FALSE #>  #> $inference_method #> [1] \"MLE\" #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"helper function creating <epidist> object create method assessment list sensible defaults, type checking arguments help remember method assessments can accepted list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"","code":"create_epidist_method_assess(   censored = NA,   right_truncated = NA,   phase_bias_adjusted = NA )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"censored boolean logical whether study used single double interval censoring methods infer delay distribution right_truncated boolean logical whether study used right- truncation methods infer delay distribution phase_bias_adjusted boolean logical whether study adjusted phase bias methods infer delay distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"named list three elements","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"Currently, method assessment focuses common methodological aspects delay distributions (e.g. incubation period, serial interval, etc.), currently take account methodological aspects may important fitting offspring distributions data disease (super)spreading.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_method_assess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify methodological aspects of distribution fitting — create_epidist_method_assess","text":"","code":"create_epidist_method_assess(   censored = FALSE,   right_truncated = FALSE,   phase_bias_adjusted = FALSE ) #> $censored #> [1] FALSE #>  #> $right_truncated #> [1] FALSE #>  #> $phase_bias_adjusted #> [1] FALSE #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a distribution object — create_epidist_prob_dist","title":"Create a distribution object — create_epidist_prob_dist","text":"Creates S3 class holding distribution parameters probability distribution name, parameters distribution truncation discretisation. class holding distribution depends whether discretised distribution. continuous discrete distributions S3 classes distributional package used, discretised continuous distributions S3 class distcrete package used. details properties distribution classes respective package see documentation (either ?distributional ?distcrete)","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a distribution object — create_epidist_prob_dist","text":"","code":"create_epidist_prob_dist(   prob_dist,   prob_dist_params,   discretise = FALSE,   truncation = NA,   ... )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a distribution object — create_epidist_prob_dist","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters. discretise boolean logical whether distribution discretised. Default FALSE assumes continuous probability distribution truncation numeric specifying truncation point inferred distribution truncated, NA unknown. ... dots Extra arguments passed distributional distcrete functions construct S3 distribution objects. see arguments can adjusted discretised distributions see distcrete::distcrete(), distributions see ?distributional documentation find specific distribution constructor function, e.g. Gamma distribution see distributional::dist_gamma().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a distribution object — create_epidist_prob_dist","text":"S3 class containing probability distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a distribution object — create_epidist_prob_dist","text":"Truncation enabled continuous distributions truncation implemented distcrete. default discretisation continuous distributions uses discretisation interval (interval) 1. unit distribution days, discretised day. endpoint weighting (w) discretisation 1. w can [0,1]. information please see distcrete::distcrete().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_prob_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a distribution object — create_epidist_prob_dist","text":"","code":"# example with continuous distribution without truncation create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = FALSE,   truncation = NA ) #> <distribution[1]> #> [1] Γ(1, 1)  # example with continuous distribution with truncation create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = FALSE,   truncation = 10 ) #> <distribution[1]> #> [1] Γ(1, 1)[-Inf,10]  # example with discrete distribution create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = TRUE,   truncation = NA ) #> A discrete distribution #>   name: gamma #>   parameters: #>     shape: 1 #>     scale: 1  # example passing extra arguments to distcrete create_epidist_prob_dist(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 1, scale = 1),   discretise = TRUE,   truncation = NA,   w = 0.5 ) #> A discrete distribution #>   name: gamma #>   parameters: #>     shape: 1 #>     scale: 1"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify the geography of the data entry — create_epidist_region","title":"Specify the geography of the data entry — create_epidist_region","text":"geography data set can single geographical region either continent, country, region city level. specifying level geography fields may deduced.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify the geography of the data entry — create_epidist_region","text":"","code":"create_epidist_region(   continent = NA_character_,   country = NA_character_,   region = NA_character_,   city = NA_character_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify the geography of the data entry — create_epidist_region","text":"continent character string specifying continent. country character string specifying country. region character string specifying region. city character string specifying city.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify the geography of the data entry — create_epidist_region","text":"named list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_region.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify the geography of the data entry — create_epidist_region","text":"","code":"create_epidist_region(country = \"UK\") #> $continent #> [1] NA #>  #> $country #> [1] \"UK\" #>  #> $region #> [1] NA #>  #> $city #> [1] NA #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify reported summary statistics — create_epidist_summary_stats","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"helper function creating <epidist> object create summary statistics list sensible defaults, type checking arguments help remember summary statistics can accepted list.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"","code":"create_epidist_summary_stats(   mean = NA_real_,   mean_ci_limits = c(NA_real_, NA_real_),   mean_ci = NA_real_,   sd = NA_real_,   sd_ci_limits = c(NA_real_, NA_real_),   sd_ci = NA_real_,   median = NA_real_,   median_ci_limits = c(NA_real_, NA_real_),   median_ci = NA_real_,   lower_range = NA_real_,   upper_range = NA_real_,   quantiles = NA_real_ )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"mean numeric mean (expectation) probability distribution. mean_ci_limits numeric vector length two confidence interval around mean. mean_ci numeric specifying confidence interval width, e.g. 95 95% CI sd numeric standard deviation probability distribution. sd_ci_limits numeric vector length 2 confidence interval around standard deviation. sd_ci numeric specifying confidence interval width, e.g. 95 95% confidence interval. median numeric median probability distribution. median_ci_limits numeric vector length two confidence interval around median. median_ci numeric specifying confidence interval width median. lower_range lower range data, used infer parameters distribution provided. upper_range upper range data, used infer parameters distribution provided. quantiles numeric vector quantiles distribution. quantiles provided default empty vector 2.5th, 5th, 25th, 75th, 95th, 97.5th quantiles supplied.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"nested list summary statistics. highest level $centre_spread $quantiles $range $dispersion","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_summary_stats.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify reported summary statistics — create_epidist_summary_stats","text":"","code":"# mean and standard deviation create_epidist_summary_stats(mean = 5, sd = 2) #> $mean #> [1] 5 #>  #> $mean_ci_limits #> [1] NA NA #>  #> $mean_ci #> [1] NA #>  #> $sd #> [1] 2 #>  #> $sd_ci_limits #> [1] NA NA #>  #> $sd_ci #> [1] NA #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] NA NA #>   # mean and standard deviation with uncertainty create_epidist_summary_stats(   mean = 4,   mean_ci_limits = c(2.1, 5.7),   mean_ci = 95,   sd = 0.7,   sd_ci_limits = c(0.3, 1.1),   sd_ci = 95 ) #> $mean #> [1] 4 #>  #> $mean_ci_limits #> [1] 2.1 5.7 #>  #> $mean_ci #> [1] 95 #>  #> $sd #> [1] 0.7 #>  #> $sd_ci_limits #> [1] 0.3 1.1 #>  #> $sd_ci #> [1] 95 #>  #> $median #> [1] NA #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1] NA NA #>   # median and range create_epidist_summary_stats(   median = 5,   lower_range = 1,   upper_range = 13 ) #> $mean #> [1] NA #>  #> $mean_ci_limits #> [1] NA NA #>  #> $mean_ci #> [1] NA #>  #> $sd #> [1] NA #>  #> $sd_ci_limits #> [1] NA NA #>  #> $sd_ci #> [1] NA #>  #> $median #> [1] 5 #>  #> $median_ci_limits #> [1] NA NA #>  #> $median_ci #> [1] NA #>  #> $quantiles #> [1] NA #>  #> $range #> [1]  1 13 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":null,"dir":"Reference","previous_headings":"","what":"Specify distribution parameter uncertainty — create_epidist_uncertainty","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"helper function creating uncertainty parameters distribution <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"","code":"create_epidist_uncertainty(ci_limits = NA_real_, ci, ci_type)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"ci_limits numeric vector length two lower upper bound confidence interval credible interval. ci numeric specifying interval ci, e.g. 95 95% ci. ci_type character string, either \"confidence interval\" \"credible interval\".","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"List three elements: $ci_limits upper lower bounds CI (either confidence interval credible interval) (.e. two element numeric vector). $ci interval (e.g. 95 95% CI) given single numeric. $ci_type character string specifying type uncertainty (can either \"confidence interval\" \"credible interval\").","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_epidist_uncertainty.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Specify distribution parameter uncertainty — create_epidist_uncertainty","text":"","code":"# example with uncertainty for a single parameter create_epidist_uncertainty(   ci_limits = c(1, 3),   ci = 95,   ci_type = \"confidence interval\" ) #> $ci_limits #> [1] 1 3 #>  #> $ci #> [1] 95 #>  #> $ci_type #> [1] \"confidence interval\" #>   # example for multiple parameters # lengh of list should match number of parameters list(   shape = create_epidist_uncertainty(     ci_limits = c(1, 3),     ci = 95,     ci_type = \"confidence interval\"   ),   scale = create_epidist_uncertainty(     ci_limits = c(2, 4),     ci = 95,     ci_type = \"confidence interval\"   ) ) #> $shape #> $shape$ci_limits #> [1] 1 3 #>  #> $shape$ci #> [1] 95 #>  #> $shape$ci_type #> [1] \"confidence interval\" #>  #>  #> $scale #> $scale$ci_limits #> [1] 2 4 #>  #> $scale$ci #> [1] 95 #>  #> $scale$ci_type #> [1] \"confidence interval\" #>  #>   # example with unknown uncertainty # the function can be called without arguments create_epidist_uncertainty() #> $ci_limits #> [1] NA #>  #> $ci #> [1] NA NA #>  #> $ci_type #> [1] NA #>  # or give NA as the first argument create_epidist_uncertainty(NA) #> $ci_limits #> [1] NA #>  #> $ci #> [1] NA NA #>  #> $ci_type #> [1] NA #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":null,"dir":"Reference","previous_headings":"","what":"Discretises a continuous distribution in an <epidist> object — discretise","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"Discretises continuous distribution <epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"","code":"discretise(x, ...)  discretize(x, ...)  # S3 method for epidist discretise(x, ...)  # S3 method for default discretise(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"x <epidist> object. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"Converts S3 distribution object <epidist> continuous (using object {distributional} package) discretised distribution (using object {distcrete} package).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Discretises a continuous distribution in an <epidist> object — discretise","text":"","code":"ebola_incubation <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing discretise(ebola_incubation) #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: discrete gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise distribution parameters — .clean_epidist_params","title":"Standardise distribution parameters — .clean_epidist_params","text":".clean_epidist_params() dispatches distribution specific parameter cleaning function depending prob_dist. example prob_dist = \"gamma\" call .clean_epidist_params_gamma().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise distribution parameters — .clean_epidist_params","text":"","code":".clean_epidist_params(prob_dist, prob_dist_params)  .clean_epidist_params_gamma(prob_dist_params)  .clean_epidist_params_lnorm(prob_dist_params)  .clean_epidist_params_nbinom(prob_dist_params)  .clean_epidist_params_geom(prob_dist_params)  .clean_epidist_params_pois(prob_dist_params)  .clean_epidist_params_norm(prob_dist_params)  .clean_epidist_params_exp(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise distribution parameters — .clean_epidist_params","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise distribution parameters — .clean_epidist_params","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_epidist_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Standardise distribution parameters — .clean_epidist_params","text":"Calling is_epidist_params() start .clean_epidist_params() ensures parameterisation incorrect error early dispatch distribution specific cleaning functions (e.g. .clean_epidist_params_gamma()). means distribution specific parameter cleaning functions need check error incorrect parameterisation.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the variables input by users — .clean_string","title":"Standardise the variables input by users — .clean_string","text":"Checks user supplied character string converts epiparameter standards: lower-case whitespace instead dashes underscores. Examples strings needing cleaned : disease pathogen names, epidemiological distributions.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the variables input by users — .clean_string","text":"","code":".clean_string(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the variables input by users — .clean_string","text":"x character string.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-clean_string.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the variables input by users — .clean_string","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"Convert shape scale parameters gamma distribution number summary statistics can calculated analytically given gamma parameters. One exception median calculated using qgamma() analytical form available.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"","code":".convert_params_gamma(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the gamma distribution to summary statistics — .convert_params_gamma","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"Convert probability (prob) geometric distribution number summary statistics can calculated analytically given geometric parameter. One exception median calculated using stats::qgeom() analytical form always unique.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"","code":".convert_params_geom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_geom.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert parameter of the geometric distribution to summary statistics — .convert_params_geom","text":"conversion function assumes distribution represents number failures first success (supported zero). form used base R distributional::dist_geometric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":null,"dir":"Reference","previous_headings":"","what":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"Converts meanlog sdlog parameters lognormal distribution number summary statistics can calculated analytically given lognormal parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"","code":".convert_params_lnorm(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_lnorm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Converts the parameters of the lognormal distribution to summary statistics — .convert_params_lnorm","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"Convert probability (prob) dispersion parameters negative binomial distribution number summary statistics can calculated analytically given negative binomial parameters. One exception median calculated using qnbinom() analytical form available. parameters prob dispersion (also commonly represented r).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"","code":".convert_params_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the negative binomial distribution to summary statistics — .convert_params_nbinom","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, ex_kurtosis.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"Convert shape scale parameters Weibull distribution number summary statistics can calculated analytically given Weibull parameters. Note conversion uses gamma() function.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"","code":".convert_params_weibull(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"... <dynamic-dots> Numeric named parameter(s) used convert summary statistics. example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_params_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the Weibull distribution to summary statistics — .convert_params_weibull","text":"list eight elements including: mean, median, mode, variance (var), standard deviation (sd), coefficient variation (cv), skewness, excess kurtosis (ex_kurtosis).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"Convert summary statistics input shape scale parameters gamma distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"","code":".convert_summary_stats_gamma(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the gamma distribution — .convert_summary_stats_gamma","text":"list two elements, shape scale","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"Convert summary statistics geometric distribution parameter (prob) geometric distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"","code":".convert_summary_stats_geom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"list one element, probability parameter.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_geom.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert summary statistics to parameters of the geometric distribution — .convert_summary_stats_geom","text":"conversion function assumes distribution represents number failures first success (supported zero). form used base R distributional::dist_geometric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"Convert summary statistics input meanlog sdlog parameters lognormal distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"","code":".convert_summary_stats_lnorm(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_lnorm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the lognormal distribution — .convert_summary_stats_lnorm","text":"list two elements: meanlog sdlog","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"Convert summary statistics negative binomial distribution parameters (prob) (dispersion) negative binomial distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"","code":".convert_summary_stats_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the negative binomial distribution — .convert_summary_stats_nbinom","text":"list two elements, probability dispersion parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"Convert summary statistics input shape scale parameters Weibull distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"","code":".convert_summary_stats_weibull(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"... <dynamic-dots> Numeric named summary statistics used convert parameter(s). example mean sd summary statistics lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-convert_summary_stats_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the Weibull distribution — .convert_summary_stats_weibull","text":"list two elements, shape scale.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"Optimises parameters specified probability distribution given percentiles distribution values percentiles, median range sample number samples.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"","code":".extract_param(values, distribution, percentiles, samples)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"values vector. type = percentiles: c(percentile_1, percentile_2); type = range: c(median, min, max). distribution character specifying distribution use. Default lnorm; also takes gamma, weibull norm. percentiles vector two elements specifying percentiles defined values using type = \"percentiles\". Percentiles specified 0 1. example 2.5th 97.5th percentile given c(0.025, 0.975). samples numeric specifying sample size using type = \"range\".","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/dot-extract_param.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Optimises the parameters for a specified probability distribution given the percentiles of a distribution and the values at those percentiles, or the median and range of a sample and the number of samples. — .extract_param","text":"list output stats::optim().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an <epidist> object — epidist","title":"Create an <epidist> object — epidist","text":"<epidist> class used store epidemiological parameters single disease. epidemiological parameters cover variety aspects including delay distributions (e.g. incubation periods serial intervals, among others) offspring distributions. <epidist> object functional unit provided {epiparameter} plug epidemiological pipelines. Obtaining <epidist> object can achieved two main ways: epidemiological distribution stored {epiparameter} library can accessed epidist_db(). alternative method information (e.g. disease distribution parameter estimates) like input <epidist> object order work existing analysis pipelines. epidist() function can used fill field information known.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an <epidist> object — epidist","text":"","code":"epidist(   disease,   pathogen = NA_character_,   epi_dist,   prob_distribution = NA_character_,   prob_distribution_params = NA_real_,   uncertainty = create_epidist_uncertainty(),   summary_stats = create_epidist_summary_stats(),   auto_calc_params = TRUE,   citation = create_epidist_citation(),   metadata = create_epidist_metadata(),   method_assess = create_epidist_method_assess(),   discretise = FALSE,   truncation = NA_real_,   notes = NULL,   ... )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an <epidist> object — epidist","text":"disease character string name infectious disease. pathogen character string name causative agent disease, NA known. epi_dist character string name epidemiological distribution type. prob_distribution character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_distribution_params named vector probability distribution parameters. uncertainty list named vectors uncertainty around probability distribution parameters. uncertainty around parameter estimates unknown use create_epidist_uncertainty() (argument default) create list correct names missing values. summary_stats list summary statistics, use create_epidist_summary_stats() create list. list can include summary statistics inferred distribution mean standard deviation, quantiles distribution, information data used fit distribution lower upper range. summary statistics can also include uncertainty around metrics confidence interval around mean standard deviation. auto_calc_params boolean logical determining whether try calculate probability distribution parameters summary statistics distribution parameters provided. Default TRUE. case sufficient summary statistics provided parameter(s) distribution , calc_dist_params() function called calculate parameters add epidist object created. citation character string citation source data paper inferred distribution parameters, use create_epidist_citation() create citation. metadata list metadata, can include: sample size, transmission mode disease (e.g. vector-borne directly transmitted), etc. assumed disease vector-borne distribution intrinsic (e.g. extrinsic delay distribution extrinsic incubation period) unless transmission_mode = \"vector_borne\" contained metadata. Use create_epidist_metadata() create metadata. method_assess list methodological aspects used fitting distribution, use create_epidist_method_assess() create method assessment. discretise boolean logical whether distribution discretised. Default FALSE assumes continuous probability distribution truncation numeric specifying truncation point inferred distribution truncated, NA unknown. notes character string additional information data, inference method disease. ... dots Extra arguments passed internal functions. commonly used pass arguments distcrete::distcrete() construct discretised distribution S3 object. see arguments can adjusted discretised distributions see distcrete::distcrete().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an <epidist> object — epidist","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an <epidist> object — epidist","text":"Accepted <epidist> distribution parameterisations : Gamma must either 'shape' 'scale' 'shape' 'rate' Weibull must 'shape' 'scale' Lognormal must 'meanlog' 'sdlog' 'mu' 'sigma' Negative Binomial must either 'mean' 'dispersion' 'n' 'p' Geometric must either 'mean' 'prob' Poisson must 'mean'","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an <epidist> object — epidist","text":"","code":"# minimal input required for `epidist` ebola_incubation <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing  # minimal input required for discrete `epidist` ebola_incubation <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1),   discretise = TRUE ) #> Citation cannot be created as author, year, journal or title is missing  # example with more fields filled in ebola_incubation <- epidist(   disease = \"ebola\",   pathogen = \"ebola_virus\",   epi_dist = \"incubation\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1),   uncertainty = create_epidist_uncertainty(),   summary_stats = create_epidist_summary_stats(     mean = 2,     sd = 1   ),   citation = create_epidist_citation(     author = person(given = \"John\", family = \"Smith\"),     year = 2002,     title = \"COVID-19 incubation period\",     journal = \"Epi Journal\",     doi = \"10.19832/j.1366-9516.2012.09147.x\"   ),   metadata = create_epidist_metadata(     sample_size = 10,     region = \"UK\",     transmission_mode = \"natural_human_to_human\",     inference_method = \"MLE\"   ),   method_assess = create_epidist_method_assess(     censored = TRUE   ),   discretise = FALSE,   truncation = NA,   notes = \"No notes\" ) #> Using Smith J (2002). “COVID-19 incubation period.” _Epi Journal_. #> doi:10.19832/j.1366-9516.2012.09147.x #> <https://doi.org/10.19832/j.1366-9516.2012.09147.x>.  #> To retrieve the citation use the 'get_citation' function"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":null,"dir":"Reference","previous_headings":"","what":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"Extract <epidist> object(s) directly library epidemiological parameters. epiparameter library epidemiological parameters compiled primary literature sources. list output epidist_db() can subset data contains, example : disease, pathogen, epidemiological distribution, sample size, region, etc. distribution specific study required, author argument can specified. Multiple entries (<epidist> objects) can returned, use arguments subset entries use single_epidist = TRUE force single <epidist> returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"","code":"epidist_db(   disease = \"all\",   pathogen = \"all\",   epi_dist = \"all\",   author = NULL,   subset = NULL,   single_epidist = FALSE )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"disease character string specifying disease. pathogen character string specifying pathogen. epi_dist character string specifying epidemiological distribution. See details full list epidemiological distributions. author character string specifying author study reporting distribution. first author matched. recommended use family name first names may may initialised. subset Either NULL valid R expressions evaluates logicals subset list <epidist>, function can applied list <epidist> objects. Subsetting (using subset) can combined subsetting done disease epidist arguments (author specified). left NULL (default) subsetting carried . subset argument similar subsetting <data.frame>, difference fixed comparisons vectorised comparisons needed. example sample_size > 10 valid subset expression, sample_size == max(sample_size), valid subset expression <data.frame> work. vectorised expression often error, likely return unexpected results. sample_size == max(sample_size) example always return TRUE (except NAs) single numeric equal max value. expression specified without using data object name (e.g. df$var) instead just var supplied. words, argument uses non-standard evaluation, just subset argument subset(), similar <data-masking> used dplyr package. single_epidist boolean logical determining whether single <epidist> multiple entries library can returned matched arguments (disease, epi_dist, author). argument used prevent multiple sets parameters returned one wanted. Note: multiple entries match arguments supplied single_epidist = TRUE <epidist> parameterised (accounts truncation available) largest sample size returned (see is_parameterised()). multiple entries equal sorting first entry returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"<epidist> object list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"disease, epi_dist author given individual arguments common variables subset parameter library . subset argument facilitates subsetting rows select <epidist> object(s) desired. subset based multiple variables separate expression &. List epidemiological distributions: \"\" (default, returns entries library) \"incubation period\" \"onset hospitalisation\" \"onset death\" \"serial interval\" \"generation time\" \"offspring distribution\" \"hospitalisation death\" \"hospitalisation discharge\" \"notification death\" \"notification discharge\" \"onset discharge\" \"onset ventilation\"","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create <epidist> object(s) directly from the epiparameter library (database) — epidist_db","text":"","code":"epidist_db(disease = \"influenza\", epi_dist = \"serial_interval\") #> Returning 1 results that match the criteria (1 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function #> Disease: Influenza #> Pathogen: Influenza-A-H1N1Pdm #> Epi Distribution: serial interval #> Study: Ghani A, Baguelin M, Griffin J, Flasche S, van Hoek A, Cauchemez S, #> Donnelly C, Robertson C, White M, Truscott J, Fraser C, Garske T, White #> P, Leach S, Hall I, Jenkins H, Ferguson N, Cooper B (2009). “The Early #> Transmission Dynamics of H1N1pdm Influenza in the United Kingdom.” #> _PLoS Currents_. doi:10.1371/currents.RRN1130 #> <https://doi.org/10.1371/currents.RRN1130>. #> Distribution: gamma #> Parameters: #>   shape: 2.622 #>   scale: 0.957  # example using custom subsetting eparam <- epidist_db(   disease = \"SARS\",   epi_dist = \"offspring_distribution\",   subset = sample_size > 40 ) #> Returning 1 results that match the criteria (1 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function  # example using functional subsetting eparam <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation_period\",   subset = is_parameterised ) #> Returning 11 results that match the criteria (11 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function  # example forcing a single <epidist> to be returned eparam <- epidist_db(   disease = \"SARS\",   epi_dist = \"offspring_distribution\",   single_epidist = TRUE ) #> Using Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>..  #> To retrieve the citation use the 'get_citation' function"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"Convert <data.frame> .data.frame.epidist() <epidist>","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"","code":"epidist_df_to_epidist(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"x <data.frame>. ... dots Extra arguments pass epidist().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_df_to_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert <data.frame> from as.data.frame.epidist() to <epidist> — epidist_df_to_epidist","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":null,"dir":"Reference","previous_headings":"","what":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"<epidist> object holds probability distribution can either continuous discrete distribution. density, cumulative distribution, quantile random number generation functions. operate distribution can included <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"","code":"# S3 method for epidist density(x, at, ...)  # S3 method for epidist cdf(x, q, ..., log = FALSE)  # S3 method for epidist quantile(x, p, ...)  # S3 method for epidist generate(x, times, ...)  # S3 method for vb_epidist density(x, at, ...)  # S3 method for vb_epidist cdf(x, q, ...)  # S3 method for vb_epidist quantile(x, p, ...)  # S3 method for vb_epidist generate(x, times, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"x <epidist> <vb_epidist> object. quantiles evaluate . ... dots Extra arguments passed method. q quantiles evaluate . log TRUE, probabilities given log probabilities. p probabilities evaluate . times number random samples.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"<epidist> object given numeric vector returned, <vb_epidist> object given list two elements numeric vector returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_distribution_functions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PDF, CDF, PMF, quantiles and random number generation for <epidist> and <vb_epidist> objects — epidist_distribution_functions","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing  # example of each distribution method for an `epidist` object stats::density(edist, at = 1) #> [1] 0.3678794 distributional::cdf(edist, q = 1) #> [1] 0.6321206 stats::quantile(edist, p = 0.2) #> [1] 0.2231436 distributional::generate(edist, times = 10) #>  [1] 3.56720380 1.16790186 0.05745463 0.34040705 3.47156091 1.04366207 #>  [7] 3.02627506 0.36756952 0.09970044 0.78957870  vb_edist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(transmission_mode = \"vector_borne\")   ),   extrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = TRUE     )   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing  # example of each distribution method for an `vb_epidist` object stats::density(vb_edist, at = 1) #> $intrinsic #> [1] 0.3678794 #>  #> $extrinsic #> [1] 0.3678794 #>  distributional::cdf(vb_edist, q = 1) #> $intrinsic #> [1] 0.6321206 #>  #> $extrinsic #> [1] 0.6321206 #>  stats::quantile(vb_edist, p = 0.2) #> $intrinsic #> [1] 0.2231436 #>  #> $extrinsic #> [1] 0.2231436 #>  distributional::generate(vb_edist, times = 10) #> $intrinsic #>  [1] 0.003006878 3.549754306 0.320788501 0.057208557 1.192544692 0.977676517 #>  [7] 0.270517553 0.632583351 0.687157296 2.307000169 #>  #> $extrinsic #>  [1] 0.5823610 0.4097386 0.4414623 0.3029223 0.3143513 0.1501912 1.9871448 #>  [8] 0.0957137 4.3464560 0.5334439 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter-package.html","id":null,"dir":"Reference","previous_headings":"","what":"epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes — epiparameter-package","title":"epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes — epiparameter-package","text":"Library epidemiological parameters infectious diseases set classes helper functions.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"epiparameter: Library of Epidemiological Parameters with Helper Functions and Classes — epiparameter-package","text":"Maintainer: Joshua W. Lambert joshua.lambert@lshtm.ac.uk (ORCID) [copyright holder] Authors: Adam Kucharski adam.kucharski@lshtm.ac.uk (ORCID) [copyright holder] Carmen Tamayo carmen.tamayo-cuartero@lshtm.ac.uk (ORCID) contributors: Hugo Gruson hugo.gruson@data.org (ORCID) [contributor, reviewer] Sebastian Funk sebastian.funk@lshtm.ac.uk (ORCID) [contributor] Pratik Gupte pratik.gupte@lshtm.ac.uk (ORCID) [reviewer]","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":null,"dir":"Reference","previous_headings":"","what":"Package options — epiparameter_options","title":"Package options — epiparameter_options","text":"Options modify printing epiparameter objects. Currently options used modify printing <multi_epidist> class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Package options — epiparameter_options","text":"","code":"epiparameter_options"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Package options — epiparameter_options","text":"object class list length 2.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparameter_options.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Package options — epiparameter_options","text":"Options set options() retrieved getOption(). options changed epiparameter package need reloaded new options taken account. Options can set .Rprofile persist across R sessions.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":null,"dir":"Reference","previous_headings":"","what":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"subset data World Health Organization Global Tuberculosis Report ...","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"","code":"epireview_core_cols"},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":"epireview-core-cols","dir":"Reference","previous_headings":"","what":"epireview_core_cols","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"character vector 56 elements data taken intersection column names disease parameter tables epireview R package.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epireview_core_cols.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"A vector of character strings with the core column names of the epidemiological parameter data exported by the epireview R package. — epireview_core_cols","text":"https://github.com/mrc-ide/epireview","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"Summary data distributions, provided reports meta-analyses, can used extract parameters chosen distribution. Currently available distributions : lognormal, gamma, Weibull normal. Extracting lognormal returns meanlog sdlog parameters, extracting gamma Weibull returns shape scale parameters, extracting normal returns mean sd parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"","code":"extract_param(   type = c(\"percentiles\", \"range\"),   values,   distribution = c(\"lnorm\", \"gamma\", \"weibull\", \"norm\"),   percentiles,   samples,   control = list(max_iter = 1000, tolerance = 1e-05) )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"type character defining whether summary statistics based around percentiles (default) range. values vector. type = percentiles: c(percentile_1, percentile_2); type = range: c(median, min, max). distribution character specifying distribution use. Default lnorm; also takes gamma, weibull norm. percentiles vector two elements specifying percentiles defined values using type = \"percentiles\". Percentiles specified 0 1. example 2.5th 97.5th percentile given c(0.025, 0.975). samples numeric specifying sample size using type = \"range\". control named list containing options optimisation. List element $max_iter numeric specifying maximum number times parameter extraction run optimisation returning result early. prevents overly long optimisation loops optimisation unstable converge multiple iterations. Default 1000 iterations. List element $tolerance passed check_optim_conv() tolerance parameter convergence iterations optimisation. Elements control list passed optim().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"named numeric vector parameter values distribution. distribution = lnorm parameters returned meanlog sdlog; distribution = gamma distribution = weibull parameters returned shape scale; distribution = norm parameters returned mean sd.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"gamma, lnorm weibull, extract_param() works strictly positive values percentiles distribution median range data (numerics supplied values argument). means negative values lower percentile lower range work function although may present epidemiological data (e.g. negative serial interval). norm distribution negative values allowed.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"Adam Kucharski, Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the parameters of a parametric probability distribution from reported values of percentiles, or median and range — extract_param","text":"","code":"# set seed to control for stochasticity set.seed(1)  # extract parameters of a lognormal distribution from the 75 percentiles extract_param(   type = \"percentiles\",   values = c(6, 13),   distribution = \"lnorm\",   percentiles = c(0.125, 0.875) ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>   meanlog     sdlog  #> 2.1783557 0.3360688   # extract parameters of a gamma distribution from median and range extract_param(   type = \"range\",   values = c(10, 3, 18),   distribution = \"gamma\",   samples = 20 ) #> Stochastic numerical optimisation used.  #> Rerun function multiple times to check global optimum is found #>    shape    scale  #> 5.342206 1.994304"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":null,"dir":"Reference","previous_headings":"","what":"Function for extracting distribution parameters — extraction_functions","title":"Function for extracting distribution parameters — extraction_functions","text":"Set functions can used estimate parameters distribution (lognormal, gamma, Weibull, normal) via optimisation either percentiles median ranges.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function for extracting distribution parameters — extraction_functions","text":"","code":"fit_range(param, val, dist = c(\"lnorm\", \"gamma\", \"weibull\", \"norm\"))  fit_percentiles(param, val, dist = c(\"lnorm\", \"gamma\", \"weibull\", \"norm\"))"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function for extracting distribution parameters — extraction_functions","text":"param Named numeric vector distribution parameters optimised. val Numeric vector, case using percentiles contains values percentiles percentiles, case median range contains median, lower range, upper range number sample points evaluate function . dist character string name distribution fitting. Naming follows base R distribution names (e.g. lnorm lognormal).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extraction_functions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Function for extracting distribution parameters — extraction_functions","text":"Adam Kucharski, Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Family method for the <epidist> class — family.epidist","title":"Family method for the <epidist> class — family.epidist","text":"family() function used extract distribution names objects {distributional} {distcrete}. method provides interface <epidist> objects give consistent output irrespective internal distribution class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Family method for the <epidist> class — family.epidist","text":"","code":"# S3 method for epidist family(object, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Family method for the <epidist> class — family.epidist","text":"object <epidist> object. ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Family method for the <epidist> class — family.epidist","text":"character string name distribution, NA <epidist> object unparameterised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/family.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Family method for the <epidist> class — family.epidist","text":"","code":"# example with continuous distribution edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing family(edist) #> [1] \"gamma\"  # example with discretised distribution edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1),   discretise = TRUE ) #> Citation cannot be created as author, year, journal or title is missing family(edist) #> [1] \"lnorm\""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Format method for <epidist> class — format.epidist","title":"Format method for <epidist> class — format.epidist","text":"Format method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format method for <epidist> class — format.epidist","text":"","code":"# S3 method for epidist format(x, header = TRUE, vb = NULL, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format method for <epidist> class — format.epidist","text":"x <epidist> object. header Boolean logical determining whether header (first part) print method printed. used internally plotting vb_epidist class vb Either NULL (default) character string either \"Intrinsic\" \"Extrinsic\" used internally plotting vb_epidist class ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for <epidist> class — format.epidist","text":"Invisibly returns <epidist>. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format method for <epidist> class — format.epidist","text":"","code":"epidist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing format(epidist) #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Format method for <vb_epidist> class — format.vb_epidist","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"Format method <vb_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"","code":"# S3 method for vb_epidist format(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"x <vb_epidist> object. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"Invisibly returns <vb_epidist>. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format method for <vb_epidist> class — format.vb_epidist","text":"","code":"vb_epidist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ),   extrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing #> Warning: Distributions in vb_epidist class are not vector-borne. Check metadata #> Warning: The extrinsic distribution is not specified extrinsic. Check metadata format(vb_epidist) #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #>  #>  <Intrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000 #>  #>  <Extrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Get citation from an <epidist> object — get_citation.epidist","title":"Get citation from an <epidist> object — get_citation.epidist","text":"Extract citation stored <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get citation from an <epidist> object — get_citation.epidist","text":"","code":"# S3 method for epidist get_citation(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get citation from an <epidist> object — get_citation.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get citation from an <epidist> object — get_citation.epidist","text":"<bibentry> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get citation from an <epidist> object — get_citation.epidist","text":"","code":"# example with <epidist> edist <- epidist_db(single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function get_citation(edist) #> Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>.  # example returning bibtex format edist <- epidist_db(disease = \"COVID-19\", single_epidist = TRUE) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function cit <- get_citation(edist) format(cit, style = \"bibtex\") #> [1] \"@Article{,\\n  author = {Natalie M. Linton and Tetsuro Kobayashi and Yichi Yang and Katsuma Hayashi and Andrei R. Akhmetzhanov and Sung-mok Jung and Baoyin Yuan and Ryo Kinoshita and Hiroshi Nishiura},\\n  year = {2020},\\n  title = {Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data},\\n  journal = {Journal of Clinical Medicine},\\n  doi = {10.3390/jcm9020538},\\n  pmid = {32079150},\\n}\""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Get citation from an object — get_citation","title":"Get citation from an object — get_citation","text":"Extract citation stored R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get citation from an object — get_citation","text":"","code":"get_citation(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get citation from an object — get_citation","text":"x object used select method. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"Extract citation stored list <epidist> objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"","code":"# S3 method for multi_epidist get_citation(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"<bibentry> object containing multiple references. length output <bibentry> equal length list <epidist> objects supplied.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.multi_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get citation from a list of <epidist> objects — get_citation.multi_epidist","text":"","code":"# example with list of <epidist> edist <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function get_citation(edist) #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-9 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-9>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-10 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-10>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-11 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-11>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-12 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-12>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-13 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-13>. #>  #> Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-14 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-14>. 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doi:10.7326/M20-0504 #> <https://doi.org/10.7326/M20-0504>. #>  #> Lauer S, Grantz K, Bi Q, Jones F, Zheng Q, Meredith H, Azman A, Reich #> N, Lessler J (2020). “The Incubation Period of Coronavirus Disease 2019 #> (COVID-19) From Publicly Reported Confirmed Cases: Estimation and #> Application.” _Annals of Internal Medicine_. doi:10.7326/M20-0504 #> <https://doi.org/10.7326/M20-0504>. #>  #> Lauer S, Grantz K, Bi Q, Jones F, Zheng Q, Meredith H, Azman A, Reich #> N, Lessler J (2020). “The Incubation Period of Coronavirus Disease 2019 #> (COVID-19) From Publicly Reported Confirmed Cases: Estimation and #> Application.” _Annals of Internal Medicine_. doi:10.7326/M20-0504 #> <https://doi.org/10.7326/M20-0504>. #>  #> Lauer S, Grantz K, Bi Q, Jones F, Zheng Q, Meredith H, Azman A, Reich #> N, Lessler J (2020). “The Incubation Period of Coronavirus Disease 2019 #> (COVID-19) From Publicly Reported Confirmed Cases: Estimation and #> Application.” _Annals of Internal Medicine_. doi:10.7326/M20-0504 #> <https://doi.org/10.7326/M20-0504>. #>  #> Guo Z, Zhao S, Sun S, He D, Chong K, Yeoh E (2022). “Estimation of the #> serial interval of monkeypox during the early outbreak in 2022.” #> _Journal of Medical Virology_. doi:10.1002/jmv.28248 #> <https://doi.org/10.1002/jmv.28248>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wang S, Zhang F, Yuan Z, Xu M, Wang Z, Gao C, Guo R, Du Z (2022). #> “Serial intervals and incubation periods of the monkeypox virus #> clades.” _Journal of Travel Medicine_. doi:10.1093/jtm/taac105 #> <https://doi.org/10.1093/jtm/taac105>. #>  #> Wei F, Peng Z, Jin Z, Wang J, Xu X, Zhang X, Xu J, Ren Z, Bai Y, Wang #> X, Lu B, Wang Z, Xu J, Huang S (2022). “Study and prediction of the #> 2022 global monkeypox epidemic.” _Journal of Biosafety and #> Biosecurity_. doi:10.1016/j.jobb.2022.12.001 #> <https://doi.org/10.1016/j.jobb.2022.12.001>. #>  #> Wei F, Peng Z, Jin Z, Wang J, Xu X, Zhang X, Xu J, Ren Z, Bai Y, Wang #> X, Lu B, Wang Z, Xu J, Huang S (2022). “Study and prediction of the #> 2022 global monkeypox epidemic.” _Journal of Biosafety and #> Biosecurity_. doi:10.1016/j.jobb.2022.12.001 #> <https://doi.org/10.1016/j.jobb.2022.12.001>. #>  #> Wei F, Peng Z, Jin Z, Wang J, Xu X, Zhang X, Xu J, Ren Z, Bai Y, Wang #> X, Lu B, Wang Z, Xu J, Huang S (2022). “Study and prediction of the #> 2022 global monkeypox epidemic.” _Journal of Biosafety and #> Biosecurity_. doi:10.1016/j.jobb.2022.12.001 #> <https://doi.org/10.1016/j.jobb.2022.12.001>."},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Get parameters from an <epidist> object — get_parameters.epidist","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"Extract parameters distribution stored <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"","code":"# S3 method for epidist get_parameters(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"named vector parameters NA <epidist> object unparameterised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"<epidist> object can unparameterised lacks probability distribution parameters probability distribution, case get_parameters.epidist() method return NA.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get parameters from an <epidist> object — get_parameters.epidist","text":"","code":"edist <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"serial interval\",   single_epidist = TRUE ) #> Using Nishiura H, Linton N, Akhmetzhanov A (2020). “Serial interval of novel #> coronavirus (COVID-19) infections.” _International Journal of #> Infectious Diseases_. doi:10.1016/j.ijid.2020.02.060 #> <https://doi.org/10.1016/j.ijid.2020.02.060>..  #> To retrieve the citation use the 'get_citation' function get_parameters(edist) #>   meanlog     sdlog  #> 1.3862617 0.5679803"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":null,"dir":"Reference","previous_headings":"","what":"Get parameters from an object — get_parameters","title":"Get parameters from an object — get_parameters","text":"Extract parameters stored R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get parameters from an object — get_parameters","text":"","code":"get_parameters(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get parameters from an object — get_parameters","text":"x object used select method. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"Parameters probability distribution can extracted using values given percentiles distribution percentiles using extract_param(). get_percentiles() takes named vector percentiles (names) values percentiles (elements vector) selects two values lower upper percentiles used extraction. lower upper percentile available NA returned. also formats vector names can correctly converted numeric using .numeric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"","code":"get_percentiles(percentiles)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"percentiles named vector values percentiles names percentiles. See Details accepted vector name format.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"named numeric vector percentiles.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert a vector of named percentiles into correct format and selects two values for parameter extraction — get_percentiles","text":"name format character value percentile. Numbers decimal places decimal point name. example 5th 95th percentile can given   2.5th 97.5th percentile can given ","code":"get_percentiles(c(\"5\" = 1, \"95\" = 10)) get_percentiles(c(\"2.5\" = 1, \"97.5\" = 10))"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"Get lower upper percentiles preference symmetrical percentiles","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"","code":"get_sym_percentiles(percentiles)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"percentiles named vector percentiles. names correct format converted numeric value using .numeric().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_sym_percentiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the lower and upper percentiles with a preference for symmetrical percentiles — get_sym_percentiles","text":"named numeric vector two elements lower (first element) upper (second element) percentiles.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if distribution in <epidist> is continuous — is_continuous","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"Check distribution <epidist> continuous","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"","code":"is_continuous(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"x <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"<epidist> class can hold <distribution> <distcrete> probability distribution objects distributional package distcrete package, respectively. <distribution> objects can continuous discrete distributions (e.g. gamma negative binomial), <distcrete> objects discrete.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_continuous.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if distribution in <epidist> is continuous — is_continuous","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1) ) #> Citation cannot be created as author, year, journal or title is missing is_continuous(edist) #> [1] TRUE is_continuous(discretise(edist)) #> [1] FALSE  edist <- epidist(   disease = \"ebola\",   epi_dist = \"offspring distribution\",   prob_distribution = \"nbinom\",   prob_distribution_params = c(mean = 2, dispersion = 0.5) ) #> Citation cannot be created as author, year, journal or title is missing is_continuous(edist) #> [1] FALSE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is an <epidist> — is_epidist","title":"Check object is an <epidist> — is_epidist","text":"Check object <epidist>","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check object is an <epidist> — is_epidist","text":"","code":"is_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check object is an <epidist> — is_epidist","text":"x R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check object is an <epidist> — is_epidist","text":"boolean logical, TRUE object <epidist> FALSE .","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check object is an <epidist> — is_epidist","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"serial_interval\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing  is_epidist(edist) #> [1] TRUE  false_edist <- list(   disease = \"ebola\",   epi_dist = \"serial_interval\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) )  is_epidist(false_edist) #> [1] FALSE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"Check <data.frame> input .data.frame.epidist()","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"","code":"is_epidist_df(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"x <data.frame>.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if <data.frame> input is from as.data.frame.epidist() — is_epidist_df","text":"single logical boolean.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"Check whether vector parameters probability distribution set possible parameters used epiparameter package","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"","code":"is_epidist_params(prob_dist, prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"check valid parameters independent whether distribution truncated discretised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epidist_params.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check whether the vector of parameters for the probability distribution are in the set of possible parameters used in the epiparameter package — is_epidist_params","text":"","code":"is_epidist_params(   prob_dist = \"gamma\",   prob_dist_params = c(shape = 2, scale = 1) ) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if <data.frame> input is from epireview — is_epireview","title":"Check if <data.frame> input is from epireview — is_epireview","text":"Check <data.frame> input epireview","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if <data.frame> input is from epireview — is_epireview","text":"","code":"is_epireview(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if <data.frame> input is from epireview — is_epireview","text":"x <data.frame>.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epireview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if <data.frame> input is from epireview — is_epireview","text":"single logical boolean.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"Check <epidist> list <epidist> objects contains distribution distribution parameters","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"","code":"is_parameterised(x, ...)  is_parameterized(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"x <epidist> list <epidist> objects. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"single boolean logical <epidist> vector logicals equal length list <epidist> objects input. <epidist> object missing either probability distribution parameters probability distribution returns FALSE, otherwise returns TRUE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if <epidist> or list of <epidist> objects contains a distribution and distribution parameters — is_parameterised","text":"","code":"# parameterised <epidist> edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing is_parameterised(edist) #> [1] TRUE  # unparameterised <epidist> edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation\" ) #> Citation cannot be created as author, year, journal or title is missing #> No adequate summary statistics available to calculate the parameters of the NA distribution #> Unparameterised <epidist> object is_parameterised(edist) #> [1] FALSE  # list of <epidist> edist <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function is_parameterised(edist) #>   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE  TRUE #>  [25]  TRUE  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [49]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [61]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [73]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE #>  [85] FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE #>  [97]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #> [109]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE #> [121] FALSE FALSE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if distribution in <epidist> is truncated — is_truncated","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"Check distribution <epidist> truncated","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"","code":"is_truncated(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"x <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"<epidist> class can hold probability distribution objects {distributional} package {distcrete} package, however, distribution objects {distributional} can truncated. <epidist> object <distcrete> object is_truncated return FALSE default.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_truncated.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if distribution in <epidist> is truncated — is_truncated","text":"","code":"edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1) ) #> Citation cannot be created as author, year, journal or title is missing is_truncated(edist) #> [1] FALSE  edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"lnorm\",   prob_distribution_params = c(meanlog = 1, sdlog = 1),   truncation = 10 ) #> Citation cannot be created as author, year, journal or title is missing is_truncated(edist) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is a <vb_epidist> — is_vb_epidist","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"Check object <vb_epidist>","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"","code":"is_vb_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"x R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"boolean logical, TRUE object <vb_epidist> FALSE .","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check object is a <vb_epidist> — is_vb_epidist","text":"","code":"vb_edist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(transmission_mode = \"vector_borne\")   ),   extrinsic_epidist = epidist(     disease = \"dengue\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = TRUE     )   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing  is_vb_epidist(vb_edist) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Mean method for <epidist> class — mean.epidist","title":"Mean method for <epidist> class — mean.epidist","text":"Mean method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mean method for <epidist> class — mean.epidist","text":"","code":"# S3 method for epidist mean(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mean method for <epidist> class — mean.epidist","text":"x <epidist> object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mean method for <epidist> class — mean.epidist","text":"numeric mean distribution NA.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Mean method for <epidist> class — mean.epidist","text":"","code":"edist <- epidist_db(   disease = \"COVID-19\",   epi_dist = \"incubation period\",   single_epidist = TRUE ) #> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan #> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other #> Epidemiological Characteristics of 2019 Novel Coronavirus Infections #> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> <https://doi.org/10.3390/jcm9020538>..  #> To retrieve the citation use the 'get_citation' function mean(edist) #> [1] 5.6"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for <epidist> class — new_epidist","title":"Constructor for <epidist> class — new_epidist","text":"Create <epidist> object. constructor search whether parameters probability distribution supplied look see whether can inferred/extracted/ converted summary statistics provided. also convert probability distribution (prob_dist) parameters (prob_dist_params) S3 class, either distribution object {distributional} discretise = FALSE, distcrete object {distcrete} discretise = TRUE.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for <epidist> class — new_epidist","text":"","code":"new_epidist(   disease = character(),   pathogen = character(),   epi_dist = character(),   prob_dist = list(),   prob_dist_params = numeric(),   uncertainty = list(),   summary_stats = list(),   auto_calc_params = logical(),   citation = character(),   metadata = list(),   method_assess = list(),   discretise = logical(),   truncation = numeric(),   notes = character(),   ... )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for <epidist> class — new_epidist","text":"disease character string name infectious disease. pathogen character string name causative agent disease, NA known. epi_dist character string name epidemiological distribution type. prob_dist character string specifying probability distribution. match R naming convention probability distributions (e.g. lognormal lnorm, negative binomial nbinom, geometric geom). prob_dist_params named vector probability distribution parameters. uncertainty list named vectors uncertainty around probability distribution parameters. uncertainty around parameter estimates unknown use create_epidist_uncertainty() (argument default) create list correct names missing values. summary_stats list summary statistics, use create_epidist_summary_stats() create list. list can include summary statistics inferred distribution mean standard deviation, quantiles distribution, information data used fit distribution lower upper range. summary statistics can also include uncertainty around metrics confidence interval around mean standard deviation. auto_calc_params boolean logical determining whether try calculate probability distribution parameters summary statistics distribution parameters provided. Default TRUE. case sufficient summary statistics provided parameter(s) distribution , calc_dist_params() function called calculate parameters add epidist object created. citation character string citation source data paper inferred distribution parameters, use create_epidist_citation() create citation. metadata list metadata, can include: sample size, transmission mode disease (e.g. vector-borne directly transmitted), etc. assumed disease vector-borne distribution intrinsic (e.g. extrinsic delay distribution extrinsic incubation period) unless transmission_mode = \"vector_borne\" contained metadata. Use create_epidist_metadata() create metadata. method_assess list methodological aspects used fitting distribution, use create_epidist_method_assess() create method assessment. discretise boolean logical whether distribution discretised. Default FALSE assumes continuous probability distribution truncation numeric specifying truncation point inferred distribution truncated, NA unknown. notes character string additional information data, inference method disease. ... dots Extra arguments passed internal functions. commonly used pass arguments distcrete::distcrete() construct discretised distribution S3 object. see arguments can adjusted discretised distributions see distcrete::distcrete().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for <epidist> class — new_epidist","text":"<epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for <vb_epidist> class — new_vb_epidist","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"Create <vb_epidist> object binding two <epidist> objects assigning <vb_epidist> class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"","code":"new_vb_epidist(intrinsic_epidist, extrinsic_epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"intrinsic_epidist <epidist> object. extrinsic_epidist <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for <vb_epidist> class — new_vb_epidist","text":"<vb_epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Table of epidemiological distributions — parameter_tbl","title":"Table of epidemiological distributions — parameter_tbl","text":"function subsets epidemiological parameter library return chosen epidemiological distribution. results returned data frame containing disease, epidemiological distribution, probability distribution, author study, year publication.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Table of epidemiological distributions — parameter_tbl","text":"","code":"parameter_tbl(   multi_epidist,   disease = \"all\",   pathogen = \"all\",   epi_dist = \"all\" )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Table of epidemiological distributions — parameter_tbl","text":"multi_epidist Either <epidist> object list <epidist> objects. disease character string name infectious disease. pathogen character string name causative agent disease, NA known. epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Table of epidemiological distributions — parameter_tbl","text":"Joshua W. Lambert, Adam Kucharski","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/parameter_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Table of epidemiological distributions — parameter_tbl","text":"","code":"epidist_list <- epidist_db(disease = \"COVID-19\") #> Returning 27 results that match the criteria (22 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function parameter_tbl(multi_epidist = epidist_list) #> # Parameter table: #> # A data frame:    27 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 COVID-19 SARS-Co… incubation peri… NA                Men e…  2020          59 #>  2 COVID-19 SARS-Co… incubation peri… NA                Rai e…  2022        6241 #>  3 COVID-19 SARS-Co… incubation peri… NA                Alene…  2021        1453 #>  4 COVID-19 SARS-Co… serial interval  NA                Alene…  2021        3924 #>  5 COVID-19 SARS-Co… serial interval  lnorm             Nishi…  2020          28 #>  6 COVID-19 SARS-Co… serial interval  weibull           Nishi…  2020          18 #>  7 COVID-19 SARS-Co… incubation peri… weibull           Yang …  2020         178 #>  8 COVID-19 SARS-Co… serial interval  norm              Yang …  2020         131 #>  9 COVID-19 SARS-Co… incubation peri… NA                Elias…  2021       28675 #> 10 COVID-19 SARS-Co… incubation peri… weibull           Bui e…  2020          19 #> # ℹ 17 more rows  # example filtering an existing list to incubation periods epidist_list <- epidist_db(disease = \"COVID-19\") #> Returning 27 results that match the criteria (22 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function parameter_tbl(   multi_epidist = epidist_list,   epi_dist = \"incubation period\" ) #> # Parameter table: #> # A data frame:    15 × 7 #>    disease  pathogen epi_distribution prob_distribution author  year sample_size #>    <chr>    <chr>    <chr>            <chr>             <chr>  <dbl>       <dbl> #>  1 COVID-19 SARS-Co… incubation peri… NA                Men e…  2020          59 #>  2 COVID-19 SARS-Co… incubation peri… NA                Rai e…  2022        6241 #>  3 COVID-19 SARS-Co… incubation peri… NA                Alene…  2021        1453 #>  4 COVID-19 SARS-Co… incubation peri… weibull           Yang …  2020         178 #>  5 COVID-19 SARS-Co… incubation peri… NA                Elias…  2021       28675 #>  6 COVID-19 SARS-Co… incubation peri… weibull           Bui e…  2020          19 #>  7 COVID-19 SARS-Co… incubation peri… lnorm             McAlo…  2020        1357 #>  8 COVID-19 SARS-Co… incubation peri… lnorm             McAlo…  2020        1269 #>  9 COVID-19 SARS-Co… incubation peri… lnorm             Linto…  2020          52 #> 10 COVID-19 SARS-Co… incubation peri… lnorm             Linto…  2020         158 #> 11 COVID-19 SARS-Co… incubation peri… lnorm             Linto…  2020          52 #> 12 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020         181 #> 13 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020          99 #> 14 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020         108 #> 15 COVID-19 SARS-Co… incubation peri… lnorm             Lauer…  2020          73"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot method for <epidist> class — plot.epidist","title":"Plot method for <epidist> class — plot.epidist","text":"Plot <epidist> object displaying either probability mass function (PMF), (case discrete distributions) probability density function (PDF) (case continuous distributions), cumulative distribution function (CDF).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot method for <epidist> class — plot.epidist","text":"","code":"# S3 method for epidist plot(x, cumulative = FALSE, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot method for <epidist> class — plot.epidist","text":"x <epidist> object. cumulative boolean logical, default FALSE. cumulative = TRUE plots cumulative distribution function (CDF). ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot method for <epidist> class — plot.epidist","text":"default xlim argument specified distribution plotted day 0 99th quantile distribution. Alternatively, numeric vector length 2 first last day plot x-axis can supplied xlim (...).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot method for <epidist> class — plot.epidist","text":"Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot method for <epidist> class — plot.epidist","text":"","code":"# plot continuous epidist edist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 2, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing plot(edist)   # plot different day range (x-axis) plot(edist, xlim = c(0, 10))   # plot CDF plot(edist, cumulative = TRUE)   # plot discrete epidist edist <- discretise(edist) plot(edist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for <epidist> class — print.epidist","title":"Print method for <epidist> class — print.epidist","text":"Print method <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for <epidist> class — print.epidist","text":"","code":"# S3 method for epidist print(x, header = TRUE, vb = NULL, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for <epidist> class — print.epidist","text":"x <epidist> object. header Boolean logical determining whether header (first part) print method printed. used internally plotting <vb_epidist> class. vb character string containing whether intrinsic (\"Intrinsic\") extrinsic (\"Extrinsic\") distribution vector-borne diseases. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for <epidist> class — print.epidist","text":"Invisibly returns <epidist>. Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for <epidist> class — print.epidist","text":"","code":"epidist <- epidist(   disease = \"ebola\",   epi_dist = \"incubation_period\",   prob_distribution = \"gamma\",   prob_distribution_params = c(shape = 1, scale = 1) ) #> Citation cannot be created as author, year, journal or title is missing epidist #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for <multi_epidist> class — print.multi_epidist","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"Print method <multi_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"","code":"# S3 method for multi_epidist print(x, ..., n = NULL)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"x <multi_epidist> object. ... dots Extra arguments passed method. n numeric specifying many <epidist> objects print. argument passed head() list printing. Default NULL number elements print controlled package options().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"Invisibly returns <multi_epidist>. Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for <multi_epidist> class — print.multi_epidist","text":"","code":"# entire database db <- epidist_db() #> Returning 122 results that match the criteria (99 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function db #> # List of 122 <epidist> objects #> Number of diseases: 23 #> ❯ Adenovirus ❯ COVID-19 ❯ Chikungunya ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ MERS ❯ Marburg Virus Disease ❯ Measles ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ RSV ❯ Rhinovirus ❯ Rift Valley Fever ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease #> Number of epi distributions: 12 #> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval #> [[1]] #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-6>. #> Distribution: lnorm #> Parameters: #>   meanlog: 1.247 #>   sdlog: 0.975 #>  #> [[2]] #> Disease: Human Coronavirus #> Pathogen: Human_Cov #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-7>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.742 #>   sdlog: 0.918 #>  #> [[3]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: incubation period #> Study: Lessler J, Reich N, Brookmeyer R, Perl T, Nelson K, Cummings D (2009). #> “Incubation periods of acute respiratory viral infections: a systematic #> review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> <https://doi.org/10.1016/S1473-3099%2809%2970069-8>. #> Distribution: lnorm #> Parameters: #>   meanlog: 0.660 #>   sdlog: 1.205 #>  #> # ℹ 119 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html  # a single disease db <- epidist_db(disease = \"Ebola\") #> Returning 17 results that match the criteria (17 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function db #> # List of 17 <epidist> objects #> Number of diseases: 1 #> ❯ Ebola Virus Disease #> Number of epi distributions: 9 #> ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ serial interval #> [[1]] #> Disease: Ebola Virus Disease #> Pathogen: Ebola Virus #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 1.500 #>   dispersion: 5.100 #>  #> [[2]] #> Disease: Ebola Virus Disease #> Pathogen: Ebola Virus-Zaire Subtype #> Epi Distribution: incubation period #> Study: Eichner M, Dowell S, Firese N (2011). “Incubation period of ebola #> hemorrhagic virus subtype zaire.” _Osong Public Health and Research #> Perspectives_. doi:10.1016/j.phrp.2011.04.001 #> <https://doi.org/10.1016/j.phrp.2011.04.001>. #> Distribution: lnorm #> Parameters: #>   meanlog: 2.487 #>   sdlog: 0.330 #>  #> [[3]] #> Disease: Ebola Virus Disease #> Pathogen: Ebola Virus-Zaire Subtype #> Epi Distribution: onset to death #> Study: The Ebola Outbreak Epidemiology Team, Barry A, Ahuka-Mundeke S, Ali #> Ahmed Y, Allarangar Y, Anoko J, Archer B, Abedi A, Bagaria J, Belizaire #> M, Bhatia S, Bokenge T, Bruni E, Cori A, Dabire E, Diallo A, Diallo B, #> Donnelly C, Dorigatti I, Dorji T, Waeber A, Fall I, Ferguson N, #> FitzJohn R, Tengomo G, Formenty P, Forna A, Fortin A, Garske T, #> Gaythorpe K, Gurry C, Hamblion E, Djingarey M, Haskew C, Hugonnet S, #> Imai N, Impouma B, Kabongo G, Kalenga O, Kibangou E, Lee T, Lukoya C, #> Ly O, Makiala-Mandanda S, Mamba A, Mbala-Kingebeni P, Mboussou F, #> Mlanda T, Makuma V, Morgan O, Mulumba A, Kakoni P, Mukadi-Bamuleka D, #> Muyembe J, Bathé N, Ndumbi Ngamala P, Ngom R, Ngoy G, Nouvellet P, Nsio #> J, Ousman K, Peron E, Polonsky J, Ryan M, Touré A, Towner R, Tshapenda #> G, Van De Weerdt R, Van Kerkhove M, Wendland A, Yao N, Yoti Z, Yuma E, #> Kalambayi Kabamba G, Mwati J, Mbuy G, Lubula L, Mutombo A, Mavila O, #> Lay Y, Kitenge E (2018). “Outbreak of Ebola virus disease in the #> Democratic Republic of the Congo, April–May, 2018: an epidemiological #> study.” _The Lancet_. doi:10.1016/S0140-6736(18)31387-4 #> <https://doi.org/10.1016/S0140-6736%2818%2931387-4>. #> Distribution: gamma #> Parameters: #>   shape: 2.400 #>   scale: 3.333 #>  #> # ℹ 14 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html  # a single epi parameter db <- epidist_db(epi_dist = \"offspring distribution\") #> Returning 10 results that match the criteria (10 are parameterised).  #> Use subset to filter by entry variables or single_epidist to return a single entry.  #> To retrieve the citation for each use the 'get_citation' function db #> # List of 10 <epidist> objects #> Number of diseases: 6 #> ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Mpox ❯ Pneumonic Plague ❯ SARS ❯ Smallpox #> Number of epi distributions: 1 #> ❯ offspring distribution #> [[1]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 1.630 #>   dispersion: 0.160 #>  #> [[2]] #> Disease: SARS #> Pathogen: SARS-Cov-1 #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 0.940 #>   dispersion: 0.170 #>  #> [[3]] #> Disease: Smallpox #> Pathogen: Smallpox-Variola-Major #> Epi Distribution: offspring distribution #> Study: Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). “Superspreading and #> the effect of individual variation on disease emergence.” _Nature_. #> doi:10.1038/nature04153 <https://doi.org/10.1038/nature04153>. #> Distribution: nbinom #> Parameters: #>   mean: 3.190 #>   dispersion: 0.370 #>  #> # ℹ 7 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/dev/articles/database.html"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for <vb_epidist> class — print.vb_epidist","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"Print method <vb_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"","code":"# S3 method for vb_epidist print(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"x <vb_epidist> object. ... dots Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"Invisibly returns <vb_epidist>. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for <vb_epidist> class — print.vb_epidist","text":"","code":"vb_epidist <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ),   extrinsic_epidist = epidist(     disease = \"ebola\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1)   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing #> Warning: Distributions in vb_epidist class are not vector-borne. Check metadata #> Warning: The extrinsic distribution is not specified extrinsic. Check metadata vb_epidist #> Disease: ebola #> Pathogen: NA #> Epi Distribution: incubation period #> Study: (????). “No citation.” #>  #>  <Intrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000 #>  #>  <Extrinsic Distribution>  #>  #> Distribution: gamma #> Parameters: #>   shape: 1.000 #>   scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. distributional cdf, generate","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for <epidist> class — validate_epidist","title":"Validator for <epidist> class — validate_epidist","text":"Validator <epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validator for <epidist> class — validate_epidist","text":"","code":"validate_epidist(epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validator for <epidist> class — validate_epidist","text":"epidist <epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validator for <epidist> class — validate_epidist","text":"Invisibly returns <epidist>. Called side-effects (errors invalid <epidist> object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for <vb_epidist> class — validate_vb_epidist","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"Validator <vb_epidist> class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"","code":"validate_vb_epidist(vb_epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"vb_epidist <vb_epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validator for <vb_epidist> class — validate_vb_epidist","text":"Invisibly returns <vb_epidist>. Called side-effects (errors invalid <vb_epidist> object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a <vb_epidist> object — vb_epidist","title":"Create a <vb_epidist> object — vb_epidist","text":"<vb_epidist> class extension <epidist> class (although subclass <epidist>). used store epidemiological parameters vector-borne diseases. methods (print(), format(), plot(), generate(), cdf(), density(), quantile()) <epidist> class therefore used identically.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a <vb_epidist> object — vb_epidist","text":"","code":"vb_epidist(intrinsic_epidist, extrinsic_epidist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a <vb_epidist> object — vb_epidist","text":"intrinsic_epidist <epidist> object. extrinsic_epidist <epidist> object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a <vb_epidist> object — vb_epidist","text":"<vb_epidist> object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a <vb_epidist> object — vb_epidist","text":"<epidist> objects contain metadata (epidist$metadata) indicating vector-borne disease (epidist$metadata$transmission_mode = \"vector_borne\") extrinsic distribution indicate metadata extrinsic distribution (epidist$metadata$extrinsic = TRUE). two aspects given construction class throw warning.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a <vb_epidist> object — vb_epidist","text":"","code":"vb <- vb_epidist(   intrinsic_epidist = epidist(     disease = \"dengue\",     pathogen = \"dengue_virus\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 1, scale = 1),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = FALSE     )   ),   extrinsic_epidist = epidist(     disease = \"dengue\",     pathogen = \"dengue_virus\",     epi_dist = \"incubation_period\",     prob_distribution = \"gamma\",     prob_distribution_params = c(shape = 2, scale = 2),     metadata = create_epidist_metadata(       transmission_mode = \"vector_borne\",       extrinsic = TRUE     )   ) ) #> Citation cannot be created as author, year, journal or title is missing #> Citation cannot be created as author, year, journal or title is missing"},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"epiparameter-development-version","dir":"Changelog","previous_headings":"","what":"epiparameter (development version)","title":"epiparameter (development version)","text":"second release {epiparameter} R package focuses interoperability {epireview} R package. Several functions refactored enhanced.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"new-features-development-version","dir":"Changelog","previous_headings":"","what":"New features","title":"epiparameter (development version)","text":"as_epidist() S3 generic added package coercion R objects <epidist> objects. as_epidist.data.frame() method added, well internal functions is_epireview() determines <data.frame> {epireview}, epireview_to_epidist() performs conversion (#298, #334 & #335) epireview_core_cols.rda data added package. used determine whether input as_epidist.data.frame() parameter table {epireview} objects recognisable class attribute (#298). new website vignette (.e. article) data_from_epireview.Rmd added explains use as_epidist() data {epireview} (#298 & #335). new vignette database.Rmd added package provide web interface {epiparameter} library epidemiological parameters. Contributed @sbfnk (#311). plotting method <epidist> objects (plot.epidist()) improved better differentiate continuous discrete discretised distributions (#315). epidist_db(..., single_epidist = TRUE) now prioritises parameter entries account right truncation (#323). create_epidist_prob_dist() (previously named create_prob_dist()) now exported enables control discretisation settings allowing arguments passed distcrete::distcrete() via ... (#324). <multi_epidist> print method (print.multi_epidist()) improved provides object information print header, first elements list elements list short, extra links advice print footer. design print method follows design pattern {pillar} (#326). <epidist> objects functions work <epidist> objects now work exponential distributions (#333). package now explicit data license: CC0 LICENSE file.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"breaking-changes-development-version","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"epiparameter (development version)","text":"list_distributions() replaced parameter_tbl() enhances printing leveraging {pillar} (#321). <vb_epidist> plotting method (plot.vb_epidist()) removed package. provided minimal functionality unnecessarily complicating function signature plot.epidist() (#315).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"bug-fixes-development-version","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"epiparameter (development version)","text":"DOI PMID lowercase throughout package resolve issues older versions R (see issue #301) (#317).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"deprecated-and-defunct-development-version","dir":"Changelog","previous_headings":"","what":"Deprecated and defunct","title":"epiparameter (development version)","text":"None","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"epiparameter-010","dir":"Changelog","previous_headings":"","what":"epiparameter 0.1.0","title":"epiparameter 0.1.0","text":"Initial release {epiparameter} R package. {epiparameter} provides: library epidemiological parameters extracted literature range diseases. Functions classes (class methods) work epidemiological parameters distributions.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"new-features-0-1-0","dir":"Changelog","previous_headings":"","what":"New features","title":"epiparameter 0.1.0","text":"library 122 epidemiological parameter set epidemiological literature. accessible package system data (sysdata.rda, epiparameter::multi_epidist) internal data (inst/extdata/parameters.json). epidist_db() function loads epidemiological parameters library. Distribution parameter conversion extraction functions (convert_params_to_summary_stats() & convert_summary_stats_to_params(), extract_param()). S3 class work epidemiological parameters <epidist>. class S3 methods aid users easily work data structures. include printing, plotting, distribution functions PDF/PMF, CDF, random number generation distribution quantiles. <epidist> class constructor function, validator function, accessors (get_*()), checkers (is_*()). also <vb_epidist> S3 class vector-borne parameters, internal <multi_epidist> class improved printing lists <epidist> objects. package contains utility functions. list_distributions() helper function provide information list <epidist> objects tabular form. calc_disc_dist_quantile() calculates quantiles probability distribution based vector probabilities time data. Five vignettes included initial release. One introduction package (epiparameter.Rmd), one tutorial converting extracting parameters (extract_convert.Rmd), one protocol used collect entries library epidemiological parameters (data_protocol.Rmd), design vignette (design_principles.Rmd), supplementary vignette quantifies bias using parameter extraction (extract_param()) {epiparameter} (extract-bias.Rmd). Unit tests documentation files. Continuous integration workflows R package checks, rendering README.md, calculating test coverage, deploying pkgdown website, updates package citation, linting package code, checking package system dependency changes, updating copyright year, validating parameter library JSON file.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"breaking-changes-0-1-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"epiparameter 0.1.0","text":"None","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"bug-fixes-0-1-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"epiparameter 0.1.0","text":"None","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/news/index.html","id":"deprecated-and-defunct-0-1-0","dir":"Changelog","previous_headings":"","what":"Deprecated and defunct","title":"epiparameter 0.1.0","text":"None","code":""}]