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Distribution functionsquantile(ebola_incubation, p = 0.5) #> [1] 8.224347 generate(ebola_incubation, times = 10) -#> [1] 0.2043956 8.5305463 11.6768496 1.9978910 13.2885969 14.6660484 -#> [7] 17.6231451 4.4941493 19.2487076 7.5612139 +#> [1] 15.462278 4.319597 14.864370 2.369793 21.906653 13.081694 13.175768 +#> [8] 16.045752 14.161657 1.614554
diff --git a/articles/extract_convert.html b/articles/extract_convert.html index e13d97eef..ccd1add5f 100644 --- a/articles/extract_convert.html +++ b/articles/extract_convert.html @@ -408,7 +408,7 @@

Extraction#> Stochastic numerical optimisation used. #> Rerun function multiple times to check global optimum is found #> shape scale -#> 3.358211 1.284183

+#> 3.358198 1.284187

In the above example we estimate parameters of the gamma distribution, but extraction is also implemented for the lognormal, normal and Weibull distributions, but specifying "lnorm", "norm" or "weibull".

A message is shown when running extract_param() to make the user aware that the estimates are not completely reliable due to the use of numerical optimisation. Rerunning the function to and finding the same parameters are returned indicates that they have successfully converged. This issue is mostly overcome by the internal setup of the extract_param() function which searches for convergence to consistent parameter estimates before returning these to the user.

The alternative extraction, by median and range, can be achieved by specifying type = "range" and using the samples argument instead of the percentiles argument. When using type = "percentiles" the samples argument is ignored and when using type = "range" the percentiles argument is ignored.

@@ -422,7 +422,7 @@

Extraction#> Stochastic numerical optimisation used. #> Rerun function multiple times to check global optimum is found #> meanlog sdlog -#> 2.302585 2.763131 +#> 2.302585 2.214994

In the above section it was mentioned that extract_param() has an internal mechanism to check that the parameters have consistently converged to the same estimates over several optimisation iterations. The tolerance of this convergence and number of times the optimisation can be repeated is specified in the control argument of extract_param(). This is set by default (tolerance = 1e-5 and max_iter = 1000), and thus does not need to be specified by the user (as shown in the above examples). In the case that the maximum number of optimisation iterations is reached, the calculation terminates returning the most recent optimisation result to the user along with a warning message.

Code
 # set seed to ensure warning is produced
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diff --git a/pkgdown.yml b/pkgdown.yml
index a7693adb1..4393ecb72 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -7,7 +7,7 @@ articles:
   epiparameter: epiparameter.html
   extract-bias: extract-bias.html
   extract_convert: extract_convert.html
-last_built: 2023-11-29T12:31Z
+last_built: 2023-11-29T14:29Z
 urls:
   reference: https://epiverse-trace.github.io/epiparameter/reference
   article: https://epiverse-trace.github.io/epiparameter/articles
diff --git a/reference/as.function.epidist.html b/reference/as.function.epidist.html
new file mode 100644
index 000000000..4a4058e29
--- /dev/null
+++ b/reference/as.function.epidist.html
@@ -0,0 +1,139 @@
+
+as.function() method for <epidist> class — as.function.epidist • epiparameter
+    Skip to contents
+    
+
+    

+

+  

+      
as.function() method for <epidist> class

+      Source: R/epidist.R
+      
as.function.epidist.Rd

+    

+
+    

+    
Converts an <epidist> object to a distribution function
+(see epidist_distribution_functions), either probability density/mass
+function, (density), cumulative distribution function (cdf), random
+number generator (generate), or quantile (quantile).

+    

+
+    

+    
Usage

+    
# S3 method for epidist
+as.function(x, func_type = c("density", "cdf", "generate", "quantile"), ...)

+    

+
+    

+    
Arguments

+    
x

+
An <epidist> object.

+
+
+
func_type

+
A single character string specifying which distribution to
+convert <epidist> object into. Default is "density". Other options are
+"cdf", "generate", or "quantile".

+
+
+
...

+
dots Extra arguments passed to or from other methods.

+
+

+    

+    
Value

+    
+
+
A function object.

+    

+    

+    
Details

+    
The function returned takes a single required argument x.

+    

+
+  

+
+
+    

+  
Developed by Joshua W. Lambert, Adam Kucharski.

+

+
+

+  
Site built with pkgdown 2.0.7.

+

+
+    

+
+  
+
+  
+
+  
+
diff --git a/reference/epidist_distribution_functions.html b/reference/epidist_distribution_functions.html
index b1696ed20..1b402d51a 100644
--- a/reference/epidist_distribution_functions.html
+++ b/reference/epidist_distribution_functions.html
@@ -174,8 +174,8 @@ 
Examplesstats::quantile(edist, p = 0.2)
 #> [1] 0.2231436
 distributional::generate(edist, times = 10)
-#>  [1] 1.10047833 0.30413406 1.03040010 1.26474259 0.67046010 0.10712752
-#>  [7] 1.32872729 0.07295741 0.81897180 0.16972258
+#>  [1] 1.20152097 0.73234245 0.17777984 0.23216526 0.55638595 1.34492014
+#>  [7] 0.05743413 1.01951737 0.79590436 0.66087427
 
 vb_edist <- vb_epidist(
   intrinsic_epidist = epidist(
@@ -223,12 +223,12 @@ 
Examples#> 
 distributional::generate(vb_edist, times = 10)
 #> $intrinsic
-#>  [1] 0.32561740 1.53778854 0.25375152 0.95776838 1.32977538 1.58407688
-#>  [7] 1.48696095 0.23943376 2.77616929 0.03676436
+#>  [1] 0.84580543 0.18903865 0.80154210 1.47069456 1.55566040 0.88198905
+#>  [7] 0.67747515 0.02203516 0.10592395 2.36671188
 #> 
 #> $extrinsic
-#>  [1] 0.3174559881 0.7988667676 0.0615454240 0.7705594070 0.2856808825
-#>  [6] 0.7236792563 1.8535510060 0.3416960916 2.1375153807 0.0007803577
+#>  [1] 0.08308844 0.88675436 0.47301726 0.13639258 0.10729928 0.72431376
+#>  [7] 0.34125024 0.96928254 1.09731310 2.25184605
 #>
diff --git a/reference/index.html b/reference/index.html index 1c6e4a6f3..2c371c9f2 100644 --- a/reference/index.html +++ b/reference/index.html @@ -98,6 +98,11 @@

epidist objectDiscretises a continuous distribution in an <epidist> object
+ as.function(<epidist>) +
+
as.function() method for <epidist> class
+
+ family(<epidist>)
Family method for the <epidist> class
diff --git a/search.json b/search.json index 8bc6f38fc..6601e306b 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to epiparameter","title":"Contributing to epiparameter","text":"outlines propose change epiparameter.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"making-changes","dir":"","previous_headings":"","what":"Making changes","title":"Contributing to epiparameter","text":"want make change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reprex (also help write unit test, needed). See bug report template. feature request see feature request.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Making changes","what":"Pull request process","title":"Contributing to epiparameter","text":"See pull request template Fork package clone onto computer. haven’t done , recommend using usethis::create_from_github(\"epiverse-trace/epiparameter\", fork = TRUE). Install development dependencies devtools::install_dev_deps(), make sure package passes R CMD check running devtools::check(). R CMD check doesn’t pass cleanly, ’s good idea ask help continuing. Create Git branch pull request (PR). recommend using usethis::pr_init(\"brief-description--change\"). Make changes, commit git, create PR running usethis::pr_push(), following prompts browser. title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet top NEWS.md (.e. just first header). Follow style described https://style.tidyverse.org/news.html.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Making changes","what":"Code style","title":"Contributing to epiparameter","text":"New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat unit tests. Contributions test cases included easier accept.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to epiparameter","text":"Please note epiparameter project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2022 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_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 short 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 short 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. 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. object can created constructor function epidist(), uncertain whether object , 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 object. list nine elements, element either single type (e.g. character), non-nested list another class. Classes elements used existing well developed infrastructure handling certain data types. $prod_dist element uses distribution class – parameterised distribution available – using either class {distributional} class {distcrete}. $citation handled using 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 designed handle multiple distributions function distribution. large number entries returned reading epidemiological parameters library using epidist_db() function, can flood console, due default list printing R. reasoning object minimal class enable cleaner descriptive printing large list objects.","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: : Contains name disease, name epidemiological distribution, parameters (available) citation information parameter source, well information. : list two 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 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 list_distributions() function. show first six rows output. list_distributions() 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 short citation for each use the 'get_citation' function epi_dist_db #> List of 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 head(list_distributions(multi_epidist = epi_dist_db)) #> disease epi_distribution prob_distribution author year #> 1 Adenovirus incubation period lnorm Justin L.... 2009 #> 2 Human Coronavirus incubation period lnorm Justin L.... 2009 #> 3 SARS incubation period lnorm Justin L.... 2009 #> 4 Influenza incubation period lnorm Justin L.... 2009 #> 5 Influenza incubation period lnorm Justin L.... 2009 #> 6 Influenza incubation period lnorm Justin L.... 2009 list_distributions(multi_epidist = epi_dist_db, disease = \"Ebola\") #> disease epi_distribution prob_distribution #> 1 Ebola Virus Disease offspring distribution nbinom #> 2 Ebola Virus Disease incubation period lnorm #> 3 Ebola Virus Disease onset to death gamma #> 4 Ebola Virus Disease incubation period gamma #> 5 Ebola Virus Disease incubation period gamma #> 6 Ebola Virus Disease incubation period gamma #> 7 Ebola Virus Disease incubation period gamma #> 8 Ebola Virus Disease serial interval gamma #> 9 Ebola Virus Disease serial interval gamma #> 10 Ebola Virus Disease serial interval gamma #> 11 Ebola Virus Disease serial interval gamma #> 12 Ebola Virus Disease hospitalisation to death gamma #> 13 Ebola Virus Disease hospitalisation to discharge gamma #> 14 Ebola Virus Disease notification to death gamma #> 15 Ebola Virus Disease notification to discharge gamma #> 16 Ebola Virus Disease onset to death gamma #> 17 Ebola Virus Disease onset to discharge gamma #> author year #> 1 J. O. Ll.... 2005 #> 2 Martin E.... 2011 #> 3 The Ebol.... 2018 #> 4 WHO Ebol.... 2015 #> 5 WHO Ebol.... 2015 #> 6 WHO Ebol.... 2015 #> 7 WHO Ebol.... 2015 #> 8 WHO Ebol.... 2015 #> 9 WHO Ebol.... 2015 #> 10 WHO Ebol.... 2015 #> 11 WHO Ebol.... 2015 #> 12 WHO Ebol.... 2015 #> 13 WHO Ebol.... 2015 #> 14 WHO Ebol.... 2015 #> 15 WHO Ebol.... 2015 #> 16 WHO Ebol.... 2015 #> 17 WHO Ebol.... 2015"},{"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 class. holds single set epidemiological parameters. 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 helper functions, e.g., ?create_epidist_citation(). Manually creating objects can especially useful new parameter estimates become available yet incorporated {epiparameter} library. seen examples vignette, class custom printing method shows disease, pathogen (known), epidemiological distribution, citation study parameters probability distribution parameter distribution (available).","code":"# from database # fetch for COVID-19 incubation period from database # return only a single covid_incubation <- epidist_db( disease = \"COVID-19\", epi_dist = \"incubation period\", single_epidist = TRUE ) #> Using McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> \"Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.\" _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> .. #> To retrieve the short citation use the 'get_citation' function covid_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> \"Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.\" _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> . #> Distribution: lnorm #> Parameters: #> meanlog: 1.660 #> sdlog: 0.480 # 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 . #> 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 . #> 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 ","title":"Getting Started with {epiparameter}","text":"providing consistent robust object store epidemiological parameters, 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 short citation for each use the 'get_citation' function #> [[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 #> . #> 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 #> . #> 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 #> . #> Distribution: lnorm #> Parameters: #> meanlog: 1.525 #> sdlog: 0.629 #> #> attr(,\"class\") #> [1] \"multi_epidist\""},{"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 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":" 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 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 #> .. #> To retrieve the short 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] 0.2043956 8.5305463 11.6768496 1.9978910 13.2885969 14.6660484 #> [7] 17.6231451 4.4941493 19.2487076 7.5612139"},{"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":" objects can easily plotted see PDF CDF distribution. default plotting range time since infection zero ten days. can altered specifying day_range argument plotting object. plotting function can useful visually comparing epidemiological distributions different publications disease. addition, plotting distribution manually creating help check parameters sensible produce expected distribution.","code":"plot(ebola_incubation) plot(ebola_incubation, day_range = 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: Figure 1: Parameter estimation bias facetted distribution. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution.","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: Figure 2: Parameter extraction bias. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution.","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\"] 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) # 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. Figure 3: Parameter extraction precision, facetted distribution. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution.","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. Figure 4: Parameter extraction precision, facetted distribution. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution. 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\"] 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) # 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. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> 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 two arguments. first (distribution) 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). currently supported summary statistic conversions {epiparameter} given distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"gamma-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Gamma distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats( distribution = \"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(distribution = \"gamma\", mean = 2, sd = 2) #> $shape #> [1] 1 #> #> $scale #> [1] 2 convert_summary_stats_to_params(distribution = \"gamma\", mean = 2, var = 2) #> $shape #> [1] 2 #> #> $scale #> [1] 1 convert_summary_stats_to_params(distribution = \"gamma\", mean = 2, cv = 2) #> $shape #> [1] 0.25 #> #> $scale #> [1] 8"},{"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( distribution = \"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(distribution = \"lnorm\", mean = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #> #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(distribution = \"lnorm\", mean = 2, var = 2) #> $meanlog #> [1] 0.4904146 #> #> $sdlog #> [1] 0.6367614 convert_summary_stats_to_params(distribution = \"lnorm\", mean = 2, cv = 2) #> $meanlog #> [1] -0.1115718 #> #> $sdlog #> [1] 1.268636 convert_summary_stats_to_params(distribution = \"lnorm\", median = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #> #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(distribution = \"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( distribution = \"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] 122.3898 convert_summary_stats_to_params(distribution = \"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(distribution = \"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(distribution = \"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( distribution = \"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(distribution = \"nbinom\", mean = 1, sd = 1) #> $prob #> [1] 1 #> #> $dispersion #> [1] Inf convert_summary_stats_to_params(distribution = \"nbinom\", mean = 1, var = 1) #> $prob #> [1] 1 #> #> $dispersion #> [1] Inf convert_summary_stats_to_params(distribution = \"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(distribution = \"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(distribution = \"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 #> 3.358211 1.284183 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 #> 2.302585 2.763131 # 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(distribution = \"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. Hugo Gruson. Contributor, reviewer. 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":"Joshua W. Lambert Adam Kucharski (2023). epiparameter: Library Epidemiological Parameters, website: https://github.com/epiverse-trace/epiparameter/","code":"@Manual{, title = {Library of Epidemiological Parameters}, author = {Joshua W. Lambert and Adam Kucharski}, year = {2023}, url = {https://github.com/epiverse-trace/epiparameter}, }"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"epiparameter-","dir":"","previous_headings":"","what":"Library of Epidemiological Parameters","title":"Library of Epidemiological Parameters","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","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","text":"load library epidemiological parameters R: results list database entries. entry library 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). object can plotted.","code":"library(epiparameter) epidists <- epidist_db() #> Returning 118 results that match the criteria (95 are parameterised). #> Use subset to filter by entry variables or single_epidist to return a single entry. #> To retrieve the short citation for each use the 'get_citation' function epidists #> List of objects #> Number of entries in library: 118 #> Number of studies in library: 45 #> Number of diseases: 23 #> Number of delay distributions: 108 #> Number of offspring distributions: 10 influenza_incubation <- epidist_db( disease = \"influenza\", epi_dist = \"incubation period\", single_epidist = TRUE ) #> Using Virlogeux V, Li M, Tsang TK, Feng L, Fang VJ, Jiang H, Wu P, Zheng J, #> Lau EHY, Cao Y, Qin Y, Liao Q, Yu H, Cowling BJ (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 .. #> To retrieve the short citation use the 'get_citation' function influenza_incubation #> Disease: Influenza #> Pathogen: Influenza-A-H7N9 #> Epi Distribution: incubation period #> Study: Virlogeux V, Li M, Tsang TK, Feng L, Fang VJ, Jiang H, Wu P, Zheng J, #> Lau EHY, Cao Y, Qin Y, Liao Q, Yu H, Cowling BJ (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 . #> Distribution: weibull #> Parameters: #> shape: 2.101 #> scale: 3.839 plot(influenza_incubation)"},{"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","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","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","text":"like contribute different epidemiological parameters stored epiparameter package, can access google sheet add data. spreadsheet contains two example entries guide fields can accept. See also data dictionary (either yaml JSON files) epiparameter package (inst/extdata) explanation accepted entries column.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"help","dir":"","previous_headings":"","what":"Help","title":"Library of Epidemiological Parameters","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","text":"Contributions epiparameter welcomed. Please follow 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","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","text":"","code":"citation(\"epiparameter\") #> To cite epiparameter in publications use: #> #> Joshua W. Lambert and Adam Kucharski (2023). epiparameter: Library of #> Epidemiological Parameters, website: #> https://github.com/epiverse-trace/epiparameter/ #> #> A BibTeX entry for LaTeX users is #> #> @Manual{, #> title = {Library of Epidemiological Parameters}, #> author = {Joshua W. Lambert and Adam Kucharski}, #> year = {2023}, #> url = {https://github.com/epiverse-trace/epiparameter}, #> }"},{"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\nof 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\nof 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\nof 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\nof 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\nof 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\nof 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\nsummary statistics — calc_dist_params","title":"Calculate the parameters of a probability distribution from a list of\nsummary 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\nsummary 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\nsummary 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\nsummary 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\nsummary 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/calc_dist_params.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the parameters of a probability distribution from a list of\nsummary statistics — calc_dist_params","text":"","code":"if (FALSE) { calc_dist_params( prob_dist = \"gamma\", summary_stats = create_epidist_summary_stats( quantiles = c(\"2.5\" = 0.2, \"97.5\" = 9.2) ), sample_size = NA ) calc_dist_params( prob_dist = \"gamma\", summary_stats = create_epidist_summary_stats( median = 5, lower_range = 3, upper_range = 12 ), sample_size = 25 ) }"},{"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\nstable value for the parameters and function output for multiple iterations — check_optim_conv","title":"Check whether the optimisation of distribution parameters has converged to\nstable 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\nstable 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\nstable 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\nstable value for the parameters and function output for multiple iterations — check_optim_conv","text":"Boolean","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the names of diseases — clean_disease","title":"Standardise the names of diseases — clean_disease","text":"Standardise names diseases","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the names of diseases — clean_disease","text":"","code":"clean_disease(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the names of diseases — clean_disease","text":"x character string specifying disease.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the names of diseases — clean_disease","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the names of epidemiological distributions — clean_epi_dist","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"Standardise names epidemiological distributions","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"","code":"clean_epi_dist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"x character string name distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"","code":"clean_epi_dist(\"Incubation_period\") #> [1] \"incubation period\""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":null,"dir":"Reference","previous_headings":"","what":"Default method if class of parameters is not recognised — clean_epidist_params.default","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"Default method class parameters recognised","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"","code":"# S3 method for default clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"Standardise parameters gamma distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"","code":"# S3 method for gamma clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"Standardise parameters geometric distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"","code":"# S3 method for geom clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"Standardise parameters lognormal distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"","code":"# S3 method for lnorm clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"Standardise parameters negative binomial distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"","code":"# S3 method for nbinom clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"Standardise parameters Normal distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"","code":"# S3 method for norm clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"Standardise parameters poisson distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"","code":"# S3 method for pois clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"Standardise parameters Weibull distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"","code":"# S3 method for weibull clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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":"... 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_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/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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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":"... 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_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/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/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/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/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":"... 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_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/convert_params_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the negative binomial distribution to summary\nstatistics — convert_params_nbinom","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — 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/convert_params_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — convert_params_nbinom","text":"","code":"convert_params_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — convert_params_nbinom","text":"... 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_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — 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/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( distribution = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"), ... )"},{"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":"distribution character string specifying distribution use. Default lnorm; also takes gamma weibull, nbinom geom. ... 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":"convert_params_to_summary_stats( distribution = \"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( distribution = \"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( distribution = \"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 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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":"... 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_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/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/convert_summary_stats_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — 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/convert_summary_stats_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","text":"","code":"convert_summary_stats_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","text":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","text":"list two elements, probability dispersion parameters.","code":""},{"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( distribution = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"), ... )"},{"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":"distribution character string specifying distribution use. Default lnorm; also takes gamma weibull, nbinom geom. ... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters 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":"convert_summary_stats_to_params(distribution = \"lnorm\", mean = 1, sd = 1) #> $meanlog #> [1] -0.3465736 #> #> $sdlog #> [1] 0.8325546 #> convert_summary_stats_to_params(distribution = \"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(distribution = \"geom\", mean = 2) #> $prob #> [1] 0.3333333 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/create_epidist_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a citation for an object — create_epidist_citation","title":"Create a citation for an object — create_epidist_citation","text":"helper function creating 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 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 object — create_epidist_citation","text":"author Either , character string, vector list characters case multiple authors. Specify full name (\"\" \"\"). using characters make sure name can converted (see .person()). Use white space separation names. Multiple names can stored within single (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 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 object — create_epidist_citation","text":" 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 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 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 #> . #> 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 #> ."},{"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 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 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_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 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 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/create_prob_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a distribution object from distribution name and parameters — create_prob_dist","title":"Create a distribution object from distribution name and parameters — create_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_prob_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"","code":"create_prob_dist(prob_dist, prob_dist_params, discretise, truncation)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a distribution object from distribution name and parameters — create_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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"S3 class containing probability distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"Truncation enabled continuous distributions truncation implemented {distcrete}.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"","code":"# \\donttest{ # example with continuous distribution without truncation epiparameter:::create_prob_dist( prob_dist = \"gamma\", prob_dist_params = c(shape = 1, scale = 1), discretise = FALSE, truncation = NA ) #> #> [1] Γ(1, 1) # example with continuous distribution with truncation epiparameter:::create_prob_dist( prob_dist = \"gamma\", prob_dist_params = c(shape = 1, scale = 1), discretise = FALSE, truncation = 10 ) #> #> [1] Γ(1, 1)[-Inf,10] # example with discrete distribution epiparameter:::create_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 # }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":null,"dir":"Reference","previous_headings":"","what":"Discretises a continuous distribution in an object — discretise","title":"Discretises a continuous distribution in an object — discretise","text":"Discretises continuous distribution 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 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 object — discretise","text":"x object. ... dots Extra arguments passed methods.","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 object — discretise","text":" 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 object — discretise","text":"Converts S3 distribution object 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 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-extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Optimises the parameters for a specified probability distribution given the\npercentiles of a distribution and the values at those percentiles, or the\nmedian and range of a sample and the number of samples. — .extract_param","title":"Optimises the parameters for a specified probability distribution given the\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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 object — epidist","title":"Create an object — epidist","text":" 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. object functional unit provided {epiparameter} plug epidemiological pipelines. Obtaining 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 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 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 object — epidist","text":"disease character string name infectious disease. pathogen character string name causative agent disease, NULL 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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an object — epidist","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an object — epidist","text":"Accepted 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 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 #> . #> 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 object(s) directly from the epiparameter library\n(database) — epidist_db","title":"Create object(s) directly from the epiparameter library\n(database) — epidist_db","text":"Extract 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 ( objects) can returned, use arguments subset entries use single_epidist = TRUE force single returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create object(s) directly from the epiparameter library\n(database) — epidist_db","text":"","code":"epidist_db( disease = \"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 object(s) directly from the epiparameter library\n(database) — epidist_db","text":"disease character string specifying disease. 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 , function can applied list objects. Subsetting (using subset) can combined subsetting done disease epidist arguments (author specified). left NULL (default) subsetting carried . subset argument similar subsetting , difference fixed comparisons vectorised comparisons needed. example sample_size > 10 valid subset expression, sample_size == max(sample_size), valid subset expression 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 used dplyr package. single_epidist boolean logical determining whether single 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 parameterised 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 object(s) directly from the epiparameter library\n(database) — epidist_db","text":" object list objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create object(s) directly from the epiparameter library\n(database) — epidist_db","text":"disease, epi_dist author given individual arguments common variables subset parameter library . subset argument facilitates subsetting rows select 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 object(s) directly from the epiparameter library\n(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 short 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 #> . #> 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 short 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 short citation for each use the 'get_citation' function # example forcing a single 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 .. #> To retrieve the short citation use the 'get_citation' function"},{"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 and\n objects — epidist_distribution_functions","title":"PDF, CDF, PMF, quantiles and random number generation for and\n objects — epidist_distribution_functions","text":" object holds probability distribution can either continuous discrete distribution. density, cumulative distribution, quantile random number generation functions. operate distribution can included 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 and\n 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 and\n objects — epidist_distribution_functions","text":"x object. quantiles evaluate . ... dots Extra arguments passed methods. 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 and\n objects — epidist_distribution_functions","text":" object given numeric vector returned, 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 and\n 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] 1.10047833 0.30413406 1.03040010 1.26474259 0.67046010 0.10712752 #> [7] 1.32872729 0.07295741 0.81897180 0.16972258 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] 0.32561740 1.53778854 0.25375152 0.95776838 1.32977538 1.58407688 #> [7] 1.48696095 0.23943376 2.77616929 0.03676436 #> #> $extrinsic #> [1] 0.3174559881 0.7988667676 0.0615454240 0.7705594070 0.2856808825 #> [6] 0.7236792563 1.8535510060 0.3416960916 2.1375153807 0.0007803577 #>"},{"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\nreported values of percentiles, or median and range — extract_param","title":"Calculate the parameters of a parametric probability distribution from\nreported 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\nreported 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\nreported 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\nreported 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\nreported 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\nreported 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\nreported 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 #> 5.339548 1.995360"},{"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 class — family.epidist","title":"Family method for the class — family.epidist","text":"family() function used extract distribution names objects {distributional} {distcrete}. method provides interface 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 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 class — family.epidist","text":"object 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 class — family.epidist","text":"character string name distribution, NA 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 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 class — format.epidist","title":"Format method for class — format.epidist","text":"Format method 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 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 class — format.epidist","text":"x 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 methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for class — format.epidist","text":"Invisibly returns . 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 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 class — format.vb_epidist","title":"Format method for class — format.vb_epidist","text":"Format method 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 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 class — format.vb_epidist","text":"x object. ... dots Extra arguments passed methods.","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 class — format.vb_epidist","text":"Invisibly returns . 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 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.” #> #> #> #> Distribution: gamma #> Parameters: #> shape: 1.000 #> scale: 1.000 #> #> #> #> Distribution: gamma #> Parameters: #> shape: 1.000 #> scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract citation information from or list of objects — get_citation","title":"Extract citation information from or list of objects — get_citation","text":"Extract citation information list objects","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract citation information from or list of objects — 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":"Extract citation information from or list of objects — get_citation","text":"x list objects. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract citation information from or list of objects — get_citation","text":"single character string list character string citations. Length list output equal number elements object passed function.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract citation information from or list of objects — get_citation","text":"","code":"# example with edist <- epidist_db(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 #> .. #> To retrieve the short citation use the 'get_citation' function get_citation(edist) #> 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 #> . # example returning bibtex format edist <- epidist_db(disease = \"COVID-19\", single_epidist = TRUE) #> Using McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> “Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.” _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> .. #> To retrieve the short citation use the 'get_citation' function cit <- get_citation(edist) format(cit, style = \"bibtex\") #> [1] \"@Article{,\\n author = {Conor McAloon and Áine Collins and Kevin Hunt and Ann Barber and Andrew W. Byrne and Francis Butler and Miriam Casey and John Griffin and Elizabeth Lane and David McEvoy and Patrick Wall and Martin Green and Luke O'Grady and Simon J. More},\\n year = {2020},\\n title = {Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research},\\n journal = {BMJ Open},\\n doi = {10.1136/bmjopen-2020-039652},\\n pmid = {32801208},\\n}\" # example with list of 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 short citation for each use the 'get_citation' function get_citation(edist) #> [[1]] #> 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 #> . #> #> [[2]] #> 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 #> . #> #> [[3]] #> 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 #> . #> #> [[4]] #> 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 #> . #> #> [[5]] #> 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 #> . #> #> [[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)70069-11 #> . #> #> [[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)70069-12 #> . #> #> [[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)70069-13 #> . #> #> [[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)70069-14 #> . #> #> [[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_. #> 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_Journal of #> Theoretical Biology_. doi:10.1016/j.jtbi.2010.12.017 #> . #> #> [[16]] #> 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 #> . #> #> [[17]] #> 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 . #> #> [[18]] #> 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 . #> #> [[19]] 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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 #> . #> #> [[73]] #> 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 #> . #> #> [[74]] #> 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 #> . #> #> [[75]] #> 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 #> . #> #> [[76]] #> 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 #> . #> #> [[77]] #> 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 #> . #> #> [[78]] #> 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 #> . #> #> [[79]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation Team (2013). “Hospital Outbreak of Middle East #> Respiratory Syndrome Coronavirus.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMoa1306742 #> . #> #> [[80]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation Team (2013). “Hospital Outbreak of Middle East #> Respiratory Syndrome Coronavirus.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMoa1306742 #> . #> #> [[81]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation Team (2013). “Hospital Outbreak of Middle East #> Respiratory Syndrome Coronavirus.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMoa1306742 #> . #> #> [[82]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation Team (2013). “Hospital Outbreak of Middle East #> Respiratory Syndrome Coronavirus.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMoa1306742 #> . #> #> [[83]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation Team (2013). “Hospital Outbreak of Middle East #> Respiratory Syndrome Coronavirus.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMoa1306742 #> . #> #> [[84]] #> Mizumoto K, Endo A, Chowell G, Miyamatsu Y, Saitoh M, Nishiura H #> (2015). “Real-time characterization of risks of death associated with #> the Middle East respiratory syndrome (MERS) in the Republic of Korea, #> 2015.” _BMC Medicine_. doi:10.1186/s12916-015-0468-3 #> . #> #> [[85]] #> Cowling B, Park M, Fang V, Wu P, Leung G, Wu J (2015). “Preliminary #> epidemiological assessment of MERS-CoV outbreak in South Korea, May to #> June 2015.” _Eurosurveillance_. #> doi:10.2807/1560-7917.es2015.20.25.21163 #> . #> #> [[86]] #> Cowling B, Park M, Fang V, Wu P, Leung G, Wu J (2015). “Preliminary #> 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“Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.” _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> . #> #> [[99]] #> 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 #> . #> #> [[100]] #> 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 #> . #> #> [[101]] #> 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 #> . #> #> [[102]] #> 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 #> . #> #> [[103]] #> 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_. 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#> with Right Truncation: A Statistical Analysis of Publicly Available #> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538 #> . #> #> [[107]] #> 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 #> . #> #> [[108]] #> 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 #> . #> #> [[109]] #> 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 #> . #> #> [[110]] #> 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 #> . #> #> [[111]] #> 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 #> . #> #> [[112]] #> 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 #> . #> #> [[113]] #> 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 #> . #> #> [[114]] #> 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 #> . #> #> [[115]] #> 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 #> . #> #> [[116]] #> 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 #> . #> #> [[117]] #> 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 #> . #> #> [[118]] #> 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 #> . #> #> [[119]] #> 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 #> . #> #> [[120]] #> 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 #> . #> #> [[121]] #> 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 #> . #> #> [[122]] #> 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 #> . #>"},{"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 distribution stored 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. ... Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get parameters from an object — get_parameters","text":"named vector parameters NA object unparameterised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get parameters from an object — get_parameters","text":" object can unparameterised lacks probability distribution parameters probability distribution. can parameters.epidist() method return NA.","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\nvalues for parameter extraction — get_percentiles","title":"Convert a vector of named percentiles into correct format and selects two\nvalues 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\nvalues 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\nvalues 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\nvalues 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\nvalues for parameter extraction — get_percentiles","text":"name format character value percentile. Numbers decimal places decimal point name (e.g. c(\"2.5\" = 1, \"97.5\" = 10)).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a vector of named percentiles into correct format and selects two\nvalues for parameter extraction — get_percentiles","text":"","code":"if (FALSE) { # 90th interval get_percentiles(c(\"5\" = 1, \"95\" = 10)) # 95th interval 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\npercentiles — get_sym_percentiles","title":"Get the lower and upper percentiles with a preference for symmetrical\npercentiles — 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\npercentiles — 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\npercentiles — 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\npercentiles — 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_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is an — is_epidist","title":"Check object is an — is_epidist","text":"Check object ","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 — 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 — 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 — is_epidist","text":"boolean logical, TRUE object 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 — 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_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the vector of parameters for the probability distribution\nare 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\nare 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\nare 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\nare 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\nare 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":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check whether the vector of parameters for the probability distribution\nare 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_parameterised.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if or list of objects contains a distribution\nand distribution parameters — is_parameterised","title":"Check if or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"Check list 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 or list of objects contains a distribution\nand 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 or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"x list objects. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"single boolean logical vector logicals equal length list objects input. 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 or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"","code":"# parameterised 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 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 object is_parameterised(edist) #> [1] FALSE # list of 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 short 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 is truncated — is_truncated","title":"Check if distribution in is truncated — is_truncated","text":"Check distribution 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 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 is truncated — is_truncated","text":"x 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 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 is truncated — is_truncated","text":" class can hold probability distribution objects {distributional} package {distcrete} package, however, distribution objects {distributional} can truncated. object 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 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 — is_vb_epidist","title":"Check object is a — is_vb_epidist","text":"Check object ","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 — 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 — 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 — is_vb_epidist","text":"boolean logical, TRUE object 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 — 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/list_distributions.html","id":null,"dir":"Reference","previous_headings":"","what":"List epidemiological distributions stored in the epiparameter library — list_distributions","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","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/list_distributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":"","code":"list_distributions(multi_epidist, disease = \"all\", epi_dist = \"all\")"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":"multi_epidist Either object list objects. disease character string name infectious disease. epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":" returned list_distributions() contains vector columns list columns. example, author column list paper can contain multiple authors.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":"Joshua W. Lambert, Adam Kucharski","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","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 short citation for each use the 'get_citation' function list_distributions(multi_epidist = epidist_list) #> disease epi_distribution prob_distribution author year #> 1 COVID-19 incubation period Ke Men, .... 2020 #> 2 COVID-19 incubation period Balram R.... 2022 #> 3 COVID-19 incubation period Muluneh .... 2021 #> 4 COVID-19 serial interval Muluneh .... 2021 #> 5 COVID-19 serial interval lnorm Hiroshi .... 2020 #> 6 COVID-19 serial interval weibull Hiroshi .... 2020 #> 7 COVID-19 incubation period weibull Lin Yang.... 2020 #> 8 COVID-19 serial interval norm Lin Yang.... 2020 #> 9 COVID-19 incubation period Christel.... 2021 #> 10 COVID-19 incubation period weibull Long V. .... 2020 #> 11 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 12 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 13 COVID-19 incubation period lnorm Natalie .... 2020 #> 14 COVID-19 incubation period lnorm Natalie .... 2020 #> 15 COVID-19 onset to hospitalisation gamma Natalie .... 2020 #> 16 COVID-19 onset to hospitalisation gamma Natalie .... 2020 #> 17 COVID-19 onset to death lnorm Natalie .... 2020 #> 18 COVID-19 hospitalisation to death weibull Natalie .... 2020 #> 19 COVID-19 incubation period lnorm Natalie .... 2020 #> 20 COVID-19 onset to hospitalisation lnorm Natalie .... 2020 #> 21 COVID-19 onset to hospitalisation lnorm Natalie .... 2020 #> 22 COVID-19 onset to death lnorm Natalie .... 2020 #> 23 COVID-19 hospitalisation to death lnorm Natalie .... 2020 #> 24 COVID-19 incubation period lnorm Stephen .... 2020 #> 25 COVID-19 incubation period lnorm Stephen .... 2020 #> 26 COVID-19 incubation period lnorm Stephen .... 2020 #> 27 COVID-19 incubation period lnorm Stephen .... 2020 # 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 short citation for each use the 'get_citation' function list_distributions( multi_epidist = epidist_list, epi_dist = \"incubation period\" ) #> disease epi_distribution prob_distribution author year #> 1 COVID-19 incubation period Ke Men, .... 2020 #> 2 COVID-19 incubation period Balram R.... 2022 #> 3 COVID-19 incubation period Muluneh .... 2021 #> 4 COVID-19 incubation period weibull Lin Yang.... 2020 #> 5 COVID-19 incubation period Christel.... 2021 #> 6 COVID-19 incubation period weibull Long V. .... 2020 #> 7 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 8 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 9 COVID-19 incubation period lnorm Natalie .... 2020 #> 10 COVID-19 incubation period lnorm Natalie .... 2020 #> 11 COVID-19 incubation period lnorm Natalie .... 2020 #> 12 COVID-19 incubation period lnorm Stephen .... 2020 #> 13 COVID-19 incubation period lnorm Stephen .... 2020 #> 14 COVID-19 incubation period lnorm Stephen .... 2020 #> 15 COVID-19 incubation period lnorm Stephen .... 2020"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Mean method for class — mean.epidist","title":"Mean method for class — mean.epidist","text":"Mean method 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 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 class — mean.epidist","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mean method for 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 class — mean.epidist","text":"","code":"edist <- epidist_db( disease = \"COVID-19\", epi_dist = \"incubation period\", single_epidist = TRUE ) #> Using McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> “Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.” _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> .. #> To retrieve the short citation use the 'get_citation' function mean(edist) #> [1] NA"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for class — new_epidist","title":"Constructor for class — new_epidist","text":"Create 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 class — new_epidist","text":"","code":"new_epidist( disease = list(), 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 class — new_epidist","text":"disease list containing $disease character string infectious disease specified study, $pathogen character string. pathogen unknown can given NULL. 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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for class — new_epidist","text":" 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 class — new_epidist","text":"","code":"epiparameter:::new_epidist( disease = list(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 class — new_vb_epidist","title":"Constructor for class — new_vb_epidist","text":"Create object binding two objects assigning 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 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 class — new_vb_epidist","text":"intrinsic_epidist object. extrinsic_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 class — new_vb_epidist","text":" object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot method for class — plot.epidist","title":"Plot method for class — plot.epidist","text":"Plot object displaying either probability mass function (PMF), (case discrete distributions) probability density function (PDF) (case continuous distributions) cumulative distribution function (CDF). Resulting 1x2 grid plot.","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 class — plot.epidist","text":"","code":"# S3 method for epidist plot(x, day_range = 0:10, ..., vb = FALSE, title = NULL)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot method for class — plot.epidist","text":"x object. day_range vector sequence days plotted x-axis distribution. ... arguments passed methods. vb boolean logical determining whether epidist plotted come vb_epidist object. title Either character string NULL. null character string printed title plot.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot method for 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 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, day_range = 0:10) # plot discrete epidist edist <- epidist( disease = \"ebola\", epi_dist = \"incubation_period\", prob_distribution = \"gamma\", prob_distribution_params = c(shape = 2, scale = 1), discretise = TRUE ) #> Citation cannot be created as author, year, journal or title is missing plot(edist, day_range = 0:10)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot method for class — plot.vb_epidist","title":"Plot method for class — plot.vb_epidist","text":"Plot object displaying either probability mass function (PMF), (case discrete distributions) probability density function (PDF) (case continuous distributions) cumulative distribution function (CDF), intrinsic extrinsic distributions. resulting 2x2 grid plot.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot method for class — plot.vb_epidist","text":"","code":"# S3 method for vb_epidist plot(x, day_range = 0:10, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot method for class — plot.vb_epidist","text":"x object. day_range vector sequence days plotted x-axis distribution. ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot method for class — plot.vb_epidist","text":"Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot method for class — plot.vb_epidist","text":"","code":"# plot vb_epidist dengue_dist <- vb_epidist( intrinsic_epidist = epidist( disease = \"dengue\", epi_dist = \"incubation\", 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\", epi_dist = \"incubation\", 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 plot(dengue_dist, day_range = 0:10)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for class — print.epidist","title":"Print method for class — print.epidist","text":"Print method 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 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 class — print.epidist","text":"x object. header Boolean logical determining whether header (first part) print method printed. used internally plotting class. vb character string containing whether intrinsic (\"Intrinsic\") extrinsic (\"Extrinsic\") distribution vector-borne diseases. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for class — print.epidist","text":"Invisibly returns . 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 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 class — print.multi_epidist","title":"Print method for class — print.multi_epidist","text":"Print method 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 class — print.multi_epidist","text":"","code":"# S3 method for multi_epidist print(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for class — print.multi_epidist","text":"x object. ... dots Extra arguments passed methods.","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 class — print.multi_epidist","text":"Invisibly returns . Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for class — print.vb_epidist","title":"Print method for class — print.vb_epidist","text":"Print method 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 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 class — print.vb_epidist","text":"x object. ... dots Extra arguments passed methods.","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 class — print.vb_epidist","text":"Invisibly returns . 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 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.” #> #> #> #> Distribution: gamma #> Parameters: #> shape: 1.000 #> scale: 1.000 #> #> #> #> 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 class — validate_epidist","title":"Validator for class — validate_epidist","text":"Validator 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 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 class — validate_epidist","text":"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 class — validate_epidist","text":"Invisibly returns . Called side-effects (errors invalid object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for class — validate_vb_epidist","title":"Validator for class — validate_vb_epidist","text":"Validator 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 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 class — validate_vb_epidist","text":"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 class — validate_vb_epidist","text":"Invisibly returns . Called side-effects (errors invalid object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a object — vb_epidist","title":"Create a object — vb_epidist","text":" class extension class (although subclass ). used store epidemiological parameters vector-borne diseases. methods (print(), format(), plot(), generate(), cdf(), density(), quantile()) 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 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 object — vb_epidist","text":"intrinsic_epidist object. extrinsic_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 object — vb_epidist","text":" object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a object — vb_epidist","text":" 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 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-010","dir":"Changelog","previous_headings":"","what":"epiparameter 0.1.0","title":"epiparameter 0.1.0","text":"Initial release {epiparameter}, R package work epidemiological parameters distributions, contains library epidemiological parameters.","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 epidemiological parameters (parameters.json) stored internal data (inst/extdata). Distribution parameter conversion extraction functions (convert_params_to_summary_stats() & convert_summary_stats_to_params(), extract_param()). S3 classes work parameters , . classes accompanied S3 methods aid users easily work data structures. include printing, plotting, distribution functions PDF/PMF, CDF, random number generation distribution quantiles. class constructor validator. package contains utility functions. Four 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) 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, 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/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to epiparameter","title":"Contributing to epiparameter","text":"outlines propose change epiparameter.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"making-changes","dir":"","previous_headings":"","what":"Making changes","title":"Contributing to epiparameter","text":"want make change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reprex (also help write unit test, needed). See bug report template. feature request see feature request.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Making changes","what":"Pull request process","title":"Contributing to epiparameter","text":"See pull request template Fork package clone onto computer. haven’t done , recommend using usethis::create_from_github(\"epiverse-trace/epiparameter\", fork = TRUE). Install development dependencies devtools::install_dev_deps(), make sure package passes R CMD check running devtools::check(). R CMD check doesn’t pass cleanly, ’s good idea ask help continuing. Create Git branch pull request (PR). recommend using usethis::pr_init(\"brief-description--change\"). Make changes, commit git, create PR running usethis::pr_push(), following prompts browser. title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet top NEWS.md (.e. just first header). Follow style described https://style.tidyverse.org/news.html.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Making changes","what":"Code style","title":"Contributing to epiparameter","text":"New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat unit tests. Contributions test cases included easier accept.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to epiparameter","text":"Please note epiparameter project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2022 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_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 short 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 short 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. 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. object can created constructor function epidist(), uncertain whether object , 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 object. list nine elements, element either single type (e.g. character), non-nested list another class. Classes elements used existing well developed infrastructure handling certain data types. $prod_dist element uses distribution class – parameterised distribution available – using either class {distributional} class {distcrete}. $citation handled using 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 designed handle multiple distributions function distribution. large number entries returned reading epidemiological parameters library using epidist_db() function, can flood console, due default list printing R. reasoning object minimal class enable cleaner descriptive printing large list objects.","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: : Contains name disease, name epidemiological distribution, parameters (available) citation information parameter source, well information. : list two 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 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 list_distributions() function. show first six rows output. list_distributions() 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 short citation for each use the 'get_citation' function epi_dist_db #> List of 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 head(list_distributions(multi_epidist = epi_dist_db)) #> disease epi_distribution prob_distribution author year #> 1 Adenovirus incubation period lnorm Justin L.... 2009 #> 2 Human Coronavirus incubation period lnorm Justin L.... 2009 #> 3 SARS incubation period lnorm Justin L.... 2009 #> 4 Influenza incubation period lnorm Justin L.... 2009 #> 5 Influenza incubation period lnorm Justin L.... 2009 #> 6 Influenza incubation period lnorm Justin L.... 2009 list_distributions(multi_epidist = epi_dist_db, disease = \"Ebola\") #> disease epi_distribution prob_distribution #> 1 Ebola Virus Disease offspring distribution nbinom #> 2 Ebola Virus Disease incubation period lnorm #> 3 Ebola Virus Disease onset to death gamma #> 4 Ebola Virus Disease incubation period gamma #> 5 Ebola Virus Disease incubation period gamma #> 6 Ebola Virus Disease incubation period gamma #> 7 Ebola Virus Disease incubation period gamma #> 8 Ebola Virus Disease serial interval gamma #> 9 Ebola Virus Disease serial interval gamma #> 10 Ebola Virus Disease serial interval gamma #> 11 Ebola Virus Disease serial interval gamma #> 12 Ebola Virus Disease hospitalisation to death gamma #> 13 Ebola Virus Disease hospitalisation to discharge gamma #> 14 Ebola Virus Disease notification to death gamma #> 15 Ebola Virus Disease notification to discharge gamma #> 16 Ebola Virus Disease onset to death gamma #> 17 Ebola Virus Disease onset to discharge gamma #> author year #> 1 J. O. Ll.... 2005 #> 2 Martin E.... 2011 #> 3 The Ebol.... 2018 #> 4 WHO Ebol.... 2015 #> 5 WHO Ebol.... 2015 #> 6 WHO Ebol.... 2015 #> 7 WHO Ebol.... 2015 #> 8 WHO Ebol.... 2015 #> 9 WHO Ebol.... 2015 #> 10 WHO Ebol.... 2015 #> 11 WHO Ebol.... 2015 #> 12 WHO Ebol.... 2015 #> 13 WHO Ebol.... 2015 #> 14 WHO Ebol.... 2015 #> 15 WHO Ebol.... 2015 #> 16 WHO Ebol.... 2015 #> 17 WHO Ebol.... 2015"},{"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 class. holds single set epidemiological parameters. 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 helper functions, e.g., ?create_epidist_citation(). Manually creating objects can especially useful new parameter estimates become available yet incorporated {epiparameter} library. seen examples vignette, class custom printing method shows disease, pathogen (known), epidemiological distribution, citation study parameters probability distribution parameter distribution (available).","code":"# from database # fetch for COVID-19 incubation period from database # return only a single covid_incubation <- epidist_db( disease = \"COVID-19\", epi_dist = \"incubation period\", single_epidist = TRUE ) #> Using McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> \"Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.\" _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> .. #> To retrieve the short citation use the 'get_citation' function covid_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> \"Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.\" _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> . #> Distribution: lnorm #> Parameters: #> meanlog: 1.660 #> sdlog: 0.480 # 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 . #> 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 . #> 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 ","title":"Getting Started with {epiparameter}","text":"providing consistent robust object store epidemiological parameters, 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 short citation for each use the 'get_citation' function #> [[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 #> . #> 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 #> . #> 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 #> . #> Distribution: lnorm #> Parameters: #> meanlog: 1.525 #> sdlog: 0.629 #> #> attr(,\"class\") #> [1] \"multi_epidist\""},{"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 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":" 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 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 #> .. #> To retrieve the short 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] 15.462278 4.319597 14.864370 2.369793 21.906653 13.081694 13.175768 #> [8] 16.045752 14.161657 1.614554"},{"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":" objects can easily plotted see PDF CDF distribution. default plotting range time since infection zero ten days. can altered specifying day_range argument plotting object. plotting function can useful visually comparing epidemiological distributions different publications disease. addition, plotting distribution manually creating help check parameters sensible produce expected distribution.","code":"plot(ebola_incubation) plot(ebola_incubation, day_range = 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: Figure 1: Parameter estimation bias facetted distribution. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution.","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: Figure 2: Parameter extraction bias. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution.","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\"] 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) # 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. Figure 3: Parameter extraction precision, facetted distribution. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution.","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. Figure 4: Parameter extraction precision, facetted distribution. Parameter 1 either shape parameter, gamma Weibull distributions, meanlog lognormal distribution. Parameter 2 either scale parameter gamma Weibull distributions, sdlog lognormal distribution. 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\"] 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) # 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. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> Warning: Maximum optimisation iterations reached, returning result early. #> Result may not be reliable. #> 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 two arguments. first (distribution) 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). currently supported summary statistic conversions {epiparameter} given distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/articles/extract_convert.html","id":"gamma-distribution","dir":"Articles","previous_headings":"Conversions > Conversion functions","what":"Gamma distribution","title":"Parameter extraction and conversion in {epiparameter}","text":"","code":"convert_params_to_summary_stats( distribution = \"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(distribution = \"gamma\", mean = 2, sd = 2) #> $shape #> [1] 1 #> #> $scale #> [1] 2 convert_summary_stats_to_params(distribution = \"gamma\", mean = 2, var = 2) #> $shape #> [1] 2 #> #> $scale #> [1] 1 convert_summary_stats_to_params(distribution = \"gamma\", mean = 2, cv = 2) #> $shape #> [1] 0.25 #> #> $scale #> [1] 8"},{"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( distribution = \"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(distribution = \"lnorm\", mean = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #> #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(distribution = \"lnorm\", mean = 2, var = 2) #> $meanlog #> [1] 0.4904146 #> #> $sdlog #> [1] 0.6367614 convert_summary_stats_to_params(distribution = \"lnorm\", mean = 2, cv = 2) #> $meanlog #> [1] -0.1115718 #> #> $sdlog #> [1] 1.268636 convert_summary_stats_to_params(distribution = \"lnorm\", median = 2, sd = 2) #> $meanlog #> [1] 0.3465736 #> #> $sdlog #> [1] 0.8325546 convert_summary_stats_to_params(distribution = \"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( distribution = \"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] 122.3898 convert_summary_stats_to_params(distribution = \"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(distribution = \"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(distribution = \"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( distribution = \"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(distribution = \"nbinom\", mean = 1, sd = 1) #> $prob #> [1] 1 #> #> $dispersion #> [1] Inf convert_summary_stats_to_params(distribution = \"nbinom\", mean = 1, var = 1) #> $prob #> [1] 1 #> #> $dispersion #> [1] Inf convert_summary_stats_to_params(distribution = \"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(distribution = \"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(distribution = \"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 #> 3.358198 1.284187 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 #> 2.302585 2.214994 # 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(distribution = \"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. Hugo Gruson. Contributor, reviewer. 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":"Joshua W. Lambert Adam Kucharski (2023). epiparameter: Library Epidemiological Parameters, website: https://github.com/epiverse-trace/epiparameter/","code":"@Manual{, title = {Library of Epidemiological Parameters}, author = {Joshua W. Lambert and Adam Kucharski}, year = {2023}, url = {https://github.com/epiverse-trace/epiparameter}, }"},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"epiparameter-","dir":"","previous_headings":"","what":"Library of Epidemiological Parameters","title":"Library of Epidemiological Parameters","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","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","text":"load library epidemiological parameters R: results list database entries. entry library 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). object can plotted.","code":"library(epiparameter) epidists <- epidist_db() #> Returning 118 results that match the criteria (95 are parameterised). #> Use subset to filter by entry variables or single_epidist to return a single entry. #> To retrieve the short citation for each use the 'get_citation' function epidists #> List of objects #> Number of entries in library: 118 #> Number of studies in library: 45 #> Number of diseases: 23 #> Number of delay distributions: 108 #> Number of offspring distributions: 10 influenza_incubation <- epidist_db( disease = \"influenza\", epi_dist = \"incubation period\", single_epidist = TRUE ) #> Using Virlogeux V, Li M, Tsang TK, Feng L, Fang VJ, Jiang H, Wu P, Zheng J, #> Lau EHY, Cao Y, Qin Y, Liao Q, Yu H, Cowling BJ (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 .. #> To retrieve the short citation use the 'get_citation' function influenza_incubation #> Disease: Influenza #> Pathogen: Influenza-A-H7N9 #> Epi Distribution: incubation period #> Study: Virlogeux V, Li M, Tsang TK, Feng L, Fang VJ, Jiang H, Wu P, Zheng J, #> Lau EHY, Cao Y, Qin Y, Liao Q, Yu H, Cowling BJ (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 . #> Distribution: weibull #> Parameters: #> shape: 2.101 #> scale: 3.839 plot(influenza_incubation)"},{"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","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","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","text":"like contribute different epidemiological parameters stored epiparameter package, can access google sheet add data. spreadsheet contains two example entries guide fields can accept. See also data dictionary (either yaml JSON files) epiparameter package (inst/extdata) explanation accepted entries column.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/index.html","id":"help","dir":"","previous_headings":"","what":"Help","title":"Library of Epidemiological Parameters","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","text":"Contributions epiparameter welcomed. Please follow 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","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","text":"","code":"citation(\"epiparameter\") #> To cite epiparameter in publications use: #> #> Joshua W. Lambert and Adam Kucharski (2023). epiparameter: Library of #> Epidemiological Parameters, website: #> https://github.com/epiverse-trace/epiparameter/ #> #> A BibTeX entry for LaTeX users is #> #> @Manual{, #> title = {Library of Epidemiological Parameters}, #> author = {Joshua W. Lambert and Adam Kucharski}, #> year = {2023}, #> url = {https://github.com/epiverse-trace/epiparameter}, #> }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"as.function() method for class — as.function.epidist","title":"as.function() method for class — as.function.epidist","text":"Converts 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 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 class — as.function.epidist","text":"x object. func_type single character string specifying distribution convert object . Default \"density\". options \"cdf\", \"generate\", \"quantile\". ... dots Extra arguments passed methods.","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 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 class — as.function.epidist","text":"function returned takes single required argument x.","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\nof 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\nof 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\nof 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\nof 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\nof 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\nof 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\nsummary statistics — calc_dist_params","title":"Calculate the parameters of a probability distribution from a list of\nsummary 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\nsummary 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\nsummary 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\nsummary 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\nsummary 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/calc_dist_params.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the parameters of a probability distribution from a list of\nsummary statistics — calc_dist_params","text":"","code":"if (FALSE) { calc_dist_params( prob_dist = \"gamma\", summary_stats = create_epidist_summary_stats( quantiles = c(\"2.5\" = 0.2, \"97.5\" = 9.2) ), sample_size = NA ) calc_dist_params( prob_dist = \"gamma\", summary_stats = create_epidist_summary_stats( median = 5, lower_range = 3, upper_range = 12 ), sample_size = 25 ) }"},{"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\nstable value for the parameters and function output for multiple iterations — check_optim_conv","title":"Check whether the optimisation of distribution parameters has converged to\nstable 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\nstable 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\nstable 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\nstable value for the parameters and function output for multiple iterations — check_optim_conv","text":"Boolean","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the names of diseases — clean_disease","title":"Standardise the names of diseases — clean_disease","text":"Standardise names diseases","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the names of diseases — clean_disease","text":"","code":"clean_disease(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the names of diseases — clean_disease","text":"x character string specifying disease.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_disease.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the names of diseases — clean_disease","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the names of epidemiological distributions — clean_epi_dist","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"Standardise names epidemiological distributions","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"","code":"clean_epi_dist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"x character string name distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epi_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Standardise the names of epidemiological distributions — clean_epi_dist","text":"","code":"clean_epi_dist(\"Incubation_period\") #> [1] \"incubation period\""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":null,"dir":"Reference","previous_headings":"","what":"Default method if class of parameters is not recognised — clean_epidist_params.default","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"Default method class parameters recognised","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"","code":"# S3 method for default clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.default.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default method if class of parameters is not recognised — clean_epidist_params.default","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"Standardise parameters gamma distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"","code":"# S3 method for gamma clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a gamma distribution — clean_epidist_params.gamma","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"Standardise parameters geometric distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"","code":"# S3 method for geom clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.geom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a geometric distribution — clean_epidist_params.geom","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"Standardise parameters lognormal distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"","code":"# S3 method for lnorm clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.lnorm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a lognormal distribution — clean_epidist_params.lnorm","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"Standardise parameters negative binomial distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"","code":"# S3 method for nbinom clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a negative binomial distribution — clean_epidist_params.nbinom","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"Standardise parameters Normal distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"","code":"# S3 method for norm clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.norm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a Normal distribution — clean_epidist_params.norm","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"Standardise parameters poisson distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"","code":"# S3 method for pois clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.pois.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a poisson distribution — clean_epidist_params.pois","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"Standardise parameters Weibull distribution","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"","code":"# S3 method for weibull clean_epidist_params(prob_dist_params)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"prob_dist_params named vector probability distribution parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_params.weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise parameters for a Weibull distribution — clean_epidist_params.weibull","text":"Named numeric vector parameters.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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":"... 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_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/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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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":"... 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_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/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/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/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/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":"... 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_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/convert_params_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert parameters of the negative binomial distribution to summary\nstatistics — convert_params_nbinom","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — 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/convert_params_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — convert_params_nbinom","text":"","code":"convert_params_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_params_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — convert_params_nbinom","text":"... 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_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert parameters of the negative binomial distribution to summary\nstatistics — 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/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( distribution = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"), ... )"},{"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":"distribution character string specifying distribution use. Default lnorm; also takes gamma weibull, nbinom geom. ... 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":"convert_params_to_summary_stats( distribution = \"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( distribution = \"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( distribution = \"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 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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":"... 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_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/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/convert_summary_stats_nbinom.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — 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/convert_summary_stats_nbinom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","text":"","code":"convert_summary_stats_nbinom(...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_nbinom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","text":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/convert_summary_stats_nbinom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert summary statistics to parameters of the negative binomial\ndistribution — convert_summary_stats_nbinom","text":"list two elements, probability dispersion parameters.","code":""},{"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( distribution = c(\"lnorm\", \"gamma\", \"weibull\", \"nbinom\", \"geom\"), ... )"},{"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":"distribution character string specifying distribution use. Default lnorm; also takes gamma weibull, nbinom geom. ... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters 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":"convert_summary_stats_to_params(distribution = \"lnorm\", mean = 1, sd = 1) #> $meanlog #> [1] -0.3465736 #> #> $sdlog #> [1] 0.8325546 #> convert_summary_stats_to_params(distribution = \"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(distribution = \"geom\", mean = 2) #> $prob #> [1] 0.3333333 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/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/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":"... Numeric named summary statistics used convert parameter(s). example meanlog sdlog parameters lognormal (lnorm) distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/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/create_epidist_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a citation for an object — create_epidist_citation","title":"Create a citation for an object — create_epidist_citation","text":"helper function creating 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 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 object — create_epidist_citation","text":"author Either , character string, vector list characters case multiple authors. Specify full name (\"\" \"\"). using characters make sure name can converted (see .person()). Use white space separation names. Multiple names can stored within single (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 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 object — create_epidist_citation","text":" 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 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 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 #> . #> 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 #> ."},{"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 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 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_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 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 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/create_prob_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a distribution object from distribution name and parameters — create_prob_dist","title":"Create a distribution object from distribution name and parameters — create_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_prob_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"","code":"create_prob_dist(prob_dist, prob_dist_params, discretise, truncation)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a distribution object from distribution name and parameters — create_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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"S3 class containing probability distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"Truncation enabled continuous distributions truncation implemented {distcrete}.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/create_prob_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a distribution object from distribution name and parameters — create_prob_dist","text":"","code":"# \\donttest{ # example with continuous distribution without truncation epiparameter:::create_prob_dist( prob_dist = \"gamma\", prob_dist_params = c(shape = 1, scale = 1), discretise = FALSE, truncation = NA ) #> #> [1] Γ(1, 1) # example with continuous distribution with truncation epiparameter:::create_prob_dist( prob_dist = \"gamma\", prob_dist_params = c(shape = 1, scale = 1), discretise = FALSE, truncation = 10 ) #> #> [1] Γ(1, 1)[-Inf,10] # example with discrete distribution epiparameter:::create_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 # }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/discretise.html","id":null,"dir":"Reference","previous_headings":"","what":"Discretises a continuous distribution in an object — discretise","title":"Discretises a continuous distribution in an object — discretise","text":"Discretises continuous distribution 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 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 object — discretise","text":"x object. ... dots Extra arguments passed methods.","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 object — discretise","text":" 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 object — discretise","text":"Converts S3 distribution object 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 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-extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Optimises the parameters for a specified probability distribution given the\npercentiles of a distribution and the values at those percentiles, or the\nmedian and range of a sample and the number of samples. — .extract_param","title":"Optimises the parameters for a specified probability distribution given the\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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\npercentiles of a distribution and the values at those percentiles, or the\nmedian 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 object — epidist","title":"Create an object — epidist","text":" 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. object functional unit provided {epiparameter} plug epidemiological pipelines. Obtaining 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 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 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 object — epidist","text":"disease character string name infectious disease. pathogen character string name causative agent disease, NULL 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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an object — epidist","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an object — epidist","text":"Accepted 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 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 #> . #> 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 object(s) directly from the epiparameter library\n(database) — epidist_db","title":"Create object(s) directly from the epiparameter library\n(database) — epidist_db","text":"Extract 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 ( objects) can returned, use arguments subset entries use single_epidist = TRUE force single returned.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create object(s) directly from the epiparameter library\n(database) — epidist_db","text":"","code":"epidist_db( disease = \"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 object(s) directly from the epiparameter library\n(database) — epidist_db","text":"disease character string specifying disease. 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 , function can applied list objects. Subsetting (using subset) can combined subsetting done disease epidist arguments (author specified). left NULL (default) subsetting carried . subset argument similar subsetting , difference fixed comparisons vectorised comparisons needed. example sample_size > 10 valid subset expression, sample_size == max(sample_size), valid subset expression 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 used dplyr package. single_epidist boolean logical determining whether single 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 parameterised 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 object(s) directly from the epiparameter library\n(database) — epidist_db","text":" object list objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create object(s) directly from the epiparameter library\n(database) — epidist_db","text":"disease, epi_dist author given individual arguments common variables subset parameter library . subset argument facilitates subsetting rows select 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 object(s) directly from the epiparameter library\n(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 short 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 #> . #> 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 short 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 short citation for each use the 'get_citation' function # example forcing a single 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 .. #> To retrieve the short citation use the 'get_citation' function"},{"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 and\n objects — epidist_distribution_functions","title":"PDF, CDF, PMF, quantiles and random number generation for and\n objects — epidist_distribution_functions","text":" object holds probability distribution can either continuous discrete distribution. density, cumulative distribution, quantile random number generation functions. operate distribution can included 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 and\n 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 and\n objects — epidist_distribution_functions","text":"x object. quantiles evaluate . ... dots Extra arguments passed methods. 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 and\n objects — epidist_distribution_functions","text":" object given numeric vector returned, 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 and\n 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] 1.20152097 0.73234245 0.17777984 0.23216526 0.55638595 1.34492014 #> [7] 0.05743413 1.01951737 0.79590436 0.66087427 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] 0.84580543 0.18903865 0.80154210 1.47069456 1.55566040 0.88198905 #> [7] 0.67747515 0.02203516 0.10592395 2.36671188 #> #> $extrinsic #> [1] 0.08308844 0.88675436 0.47301726 0.13639258 0.10729928 0.72431376 #> [7] 0.34125024 0.96928254 1.09731310 2.25184605 #>"},{"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\nreported values of percentiles, or median and range — extract_param","title":"Calculate the parameters of a parametric probability distribution from\nreported 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\nreported 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\nreported 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\nreported 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\nreported 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\nreported 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\nreported 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 #> 5.339548 1.995360"},{"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 class — family.epidist","title":"Family method for the class — family.epidist","text":"family() function used extract distribution names objects {distributional} {distcrete}. method provides interface 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 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 class — family.epidist","text":"object 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 class — family.epidist","text":"character string name distribution, NA 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 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 class — format.epidist","title":"Format method for class — format.epidist","text":"Format method 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 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 class — format.epidist","text":"x 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 methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for class — format.epidist","text":"Invisibly returns . 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 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 class — format.vb_epidist","title":"Format method for class — format.vb_epidist","text":"Format method 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 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 class — format.vb_epidist","text":"x object. ... dots Extra arguments passed methods.","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 class — format.vb_epidist","text":"Invisibly returns . 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 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.” #> #> #> #> Distribution: gamma #> Parameters: #> shape: 1.000 #> scale: 1.000 #> #> #> #> Distribution: gamma #> Parameters: #> shape: 1.000 #> scale: 1.000"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract citation information from or list of objects — get_citation","title":"Extract citation information from or list of objects — get_citation","text":"Extract citation information list objects","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract citation information from or list of objects — 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":"Extract citation information from or list of objects — get_citation","text":"x list objects. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract citation information from or list of objects — get_citation","text":"single character string list character string citations. Length list output equal number elements object passed function.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_citation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract citation information from or list of objects — get_citation","text":"","code":"# example with edist <- epidist_db(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 #> .. #> To retrieve the short citation use the 'get_citation' function get_citation(edist) #> 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 #> . # example returning bibtex format edist <- epidist_db(disease = \"COVID-19\", single_epidist = TRUE) #> Using McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> “Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.” _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> .. #> To retrieve the short citation use the 'get_citation' function cit <- get_citation(edist) format(cit, style = \"bibtex\") #> [1] \"@Article{,\\n author = {Conor McAloon and Áine Collins and Kevin Hunt and Ann Barber and Andrew W. Byrne and Francis Butler and Miriam Casey and John Griffin and Elizabeth Lane and David McEvoy and Patrick Wall and Martin Green and Luke O'Grady and Simon J. More},\\n year = {2020},\\n title = {Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research},\\n journal = {BMJ Open},\\n doi = {10.1136/bmjopen-2020-039652},\\n pmid = {32801208},\\n}\" # example with list of 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 short citation for each use the 'get_citation' function get_citation(edist) #> [[1]] #> 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 #> . #> #> [[2]] #> 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 #> . #> #> [[3]] #> 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 #> . #> #> [[4]] #> 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 #> . #> #> [[5]] #> 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 #> . #> #> [[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)70069-11 #> . #> #> [[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)70069-12 #> . #> #> [[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)70069-13 #> . #> #> [[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)70069-14 #> . #> #> [[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)70069-15 #> . #> #> [[11]] #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 . #> #> [[12]] #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 . #> #> [[13]] #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 . #> #> [[14]] #> Reich N, Lessler J, Cummings D, Brookmeyer R (2009). “Estimating #> incubation period distributions with coarse data.” _Statistics in #> Medicine_. doi:10.1002/sim.3659 . #> #> [[15]] #> 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.” 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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 #> . #> #> [[73]] #> 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 #> . #> #> [[74]] #> 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 #> . #> #> [[75]] #> 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 #> . #> #> [[76]] #> 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 #> . #> #> [[77]] #> 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 #> . #> #> [[78]] #> 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 #> . #> #> [[79]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation Team (2013). “Hospital Outbreak of Middle East #> Respiratory Syndrome Coronavirus.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMoa1306742 #> . #> #> [[80]] #> Assiri A, McGeer A, Perl T, Price C, Al Rabeeah A, Cummings D, #> Alabdullatif Z, Assad M, Almulhim A, Makhdoom H, Madani H, Alhakeem R, #> Al-Tawfiq J, Cotten M, Watson S, Kellam P, Zumla A, Memish Z, KSA #> MERSCOV Investigation 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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. ... Extra arguments passed method.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get parameters from an object — get_parameters","text":"named vector parameters NA object unparameterised.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_parameters.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get parameters from an object — get_parameters","text":" object can unparameterised lacks probability distribution parameters probability distribution. can parameters.epidist() method return NA.","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\nvalues for parameter extraction — get_percentiles","title":"Convert a vector of named percentiles into correct format and selects two\nvalues 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\nvalues 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\nvalues 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\nvalues 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\nvalues for parameter extraction — get_percentiles","text":"name format character value percentile. Numbers decimal places decimal point name (e.g. c(\"2.5\" = 1, \"97.5\" = 10)).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/get_percentiles.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a vector of named percentiles into correct format and selects two\nvalues for parameter extraction — get_percentiles","text":"","code":"if (FALSE) { # 90th interval get_percentiles(c(\"5\" = 1, \"95\" = 10)) # 95th interval 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\npercentiles — get_sym_percentiles","title":"Get the lower and upper percentiles with a preference for symmetrical\npercentiles — 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\npercentiles — 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\npercentiles — 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\npercentiles — 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_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is an — is_epidist","title":"Check object is an — is_epidist","text":"Check object ","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 — 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 — 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 — is_epidist","text":"boolean logical, TRUE object 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 — 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_params.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the vector of parameters for the probability distribution\nare 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\nare 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\nare 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\nare 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\nare 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":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check whether the vector of parameters for the probability distribution\nare 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_parameterised.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if or list of objects contains a distribution\nand distribution parameters — is_parameterised","title":"Check if or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"Check list 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 or list of objects contains a distribution\nand 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 or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"x list objects. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"single boolean logical vector logicals equal length list objects input. 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 or list of objects contains a distribution\nand distribution parameters — is_parameterised","text":"","code":"# parameterised 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 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 object is_parameterised(edist) #> [1] FALSE # list of 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 short 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 is truncated — is_truncated","title":"Check if distribution in is truncated — is_truncated","text":"Check distribution 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 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 is truncated — is_truncated","text":"x 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 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 is truncated — is_truncated","text":" class can hold probability distribution objects {distributional} package {distcrete} package, however, distribution objects {distributional} can truncated. object 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 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 — is_vb_epidist","title":"Check object is a — is_vb_epidist","text":"Check object ","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 — 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 — 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 — is_vb_epidist","text":"boolean logical, TRUE object 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 — 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/list_distributions.html","id":null,"dir":"Reference","previous_headings":"","what":"List epidemiological distributions stored in the epiparameter library — list_distributions","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","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/list_distributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":"","code":"list_distributions(multi_epidist, disease = \"all\", epi_dist = \"all\")"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":"multi_epidist Either object list objects. disease character string name infectious disease. epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":" returned list_distributions() contains vector columns list columns. example, author column list paper can contain multiple authors.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","text":"Joshua W. Lambert, Adam Kucharski","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/list_distributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List epidemiological distributions stored in the epiparameter library — list_distributions","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 short citation for each use the 'get_citation' function list_distributions(multi_epidist = epidist_list) #> disease epi_distribution prob_distribution author year #> 1 COVID-19 incubation period Ke Men, .... 2020 #> 2 COVID-19 incubation period Balram R.... 2022 #> 3 COVID-19 incubation period Muluneh .... 2021 #> 4 COVID-19 serial interval Muluneh .... 2021 #> 5 COVID-19 serial interval lnorm Hiroshi .... 2020 #> 6 COVID-19 serial interval weibull Hiroshi .... 2020 #> 7 COVID-19 incubation period weibull Lin Yang.... 2020 #> 8 COVID-19 serial interval norm Lin Yang.... 2020 #> 9 COVID-19 incubation period Christel.... 2021 #> 10 COVID-19 incubation period weibull Long V. .... 2020 #> 11 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 12 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 13 COVID-19 incubation period lnorm Natalie .... 2020 #> 14 COVID-19 incubation period lnorm Natalie .... 2020 #> 15 COVID-19 onset to hospitalisation gamma Natalie .... 2020 #> 16 COVID-19 onset to hospitalisation gamma Natalie .... 2020 #> 17 COVID-19 onset to death lnorm Natalie .... 2020 #> 18 COVID-19 hospitalisation to death weibull Natalie .... 2020 #> 19 COVID-19 incubation period lnorm Natalie .... 2020 #> 20 COVID-19 onset to hospitalisation lnorm Natalie .... 2020 #> 21 COVID-19 onset to hospitalisation lnorm Natalie .... 2020 #> 22 COVID-19 onset to death lnorm Natalie .... 2020 #> 23 COVID-19 hospitalisation to death lnorm Natalie .... 2020 #> 24 COVID-19 incubation period lnorm Stephen .... 2020 #> 25 COVID-19 incubation period lnorm Stephen .... 2020 #> 26 COVID-19 incubation period lnorm Stephen .... 2020 #> 27 COVID-19 incubation period lnorm Stephen .... 2020 # 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 short citation for each use the 'get_citation' function list_distributions( multi_epidist = epidist_list, epi_dist = \"incubation period\" ) #> disease epi_distribution prob_distribution author year #> 1 COVID-19 incubation period Ke Men, .... 2020 #> 2 COVID-19 incubation period Balram R.... 2022 #> 3 COVID-19 incubation period Muluneh .... 2021 #> 4 COVID-19 incubation period weibull Lin Yang.... 2020 #> 5 COVID-19 incubation period Christel.... 2021 #> 6 COVID-19 incubation period weibull Long V. .... 2020 #> 7 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 8 COVID-19 incubation period lnorm Conor Mc.... 2020 #> 9 COVID-19 incubation period lnorm Natalie .... 2020 #> 10 COVID-19 incubation period lnorm Natalie .... 2020 #> 11 COVID-19 incubation period lnorm Natalie .... 2020 #> 12 COVID-19 incubation period lnorm Stephen .... 2020 #> 13 COVID-19 incubation period lnorm Stephen .... 2020 #> 14 COVID-19 incubation period lnorm Stephen .... 2020 #> 15 COVID-19 incubation period lnorm Stephen .... 2020"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Mean method for class — mean.epidist","title":"Mean method for class — mean.epidist","text":"Mean method 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 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 class — mean.epidist","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/mean.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mean method for 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 class — mean.epidist","text":"","code":"edist <- epidist_db( disease = \"COVID-19\", epi_dist = \"incubation period\", single_epidist = TRUE ) #> Using McAloon C, Collins Á, Hunt K, Barber A, Byrne A, Butler F, Casey M, #> Griffin J, Lane E, McEvoy D, Wall P, Green M, O'Grady L, More S (2020). #> “Incubation period of COVID-19: a rapid systematic review and #> meta-analysis of observational research.” _BMJ Open_. #> doi:10.1136/bmjopen-2020-039652 #> .. #> To retrieve the short citation use the 'get_citation' function mean(edist) #> [1] NA"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for class — new_epidist","title":"Constructor for class — new_epidist","text":"Create 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 class — new_epidist","text":"","code":"new_epidist( disease = list(), 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 class — new_epidist","text":"disease list containing $disease character string infectious disease specified study, $pathogen character string. pathogen unknown can given NULL. 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.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for class — new_epidist","text":" 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 class — new_epidist","text":"","code":"epiparameter:::new_epidist( disease = list(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 class — new_vb_epidist","title":"Constructor for class — new_vb_epidist","text":"Create object binding two objects assigning 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 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 class — new_vb_epidist","text":"intrinsic_epidist object. extrinsic_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 class — new_vb_epidist","text":" object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot method for class — plot.epidist","title":"Plot method for class — plot.epidist","text":"Plot object displaying either probability mass function (PMF), (case discrete distributions) probability density function (PDF) (case continuous distributions) cumulative distribution function (CDF). Resulting 1x2 grid plot.","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 class — plot.epidist","text":"","code":"# S3 method for epidist plot(x, day_range = 0:10, ..., vb = FALSE, title = NULL)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot method for class — plot.epidist","text":"x object. day_range vector sequence days plotted x-axis distribution. ... arguments passed methods. vb boolean logical determining whether epidist plotted come vb_epidist object. title Either character string NULL. null character string printed title plot.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.epidist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot method for 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 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, day_range = 0:10) # plot discrete epidist edist <- epidist( disease = \"ebola\", epi_dist = \"incubation_period\", prob_distribution = \"gamma\", prob_distribution_params = c(shape = 2, scale = 1), discretise = TRUE ) #> Citation cannot be created as author, year, journal or title is missing plot(edist, day_range = 0:10)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot method for class — plot.vb_epidist","title":"Plot method for class — plot.vb_epidist","text":"Plot object displaying either probability mass function (PMF), (case discrete distributions) probability density function (PDF) (case continuous distributions) cumulative distribution function (CDF), intrinsic extrinsic distributions. resulting 2x2 grid plot.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot method for class — plot.vb_epidist","text":"","code":"# S3 method for vb_epidist plot(x, day_range = 0:10, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot method for class — plot.vb_epidist","text":"x object. day_range vector sequence days plotted x-axis distribution. ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot method for class — plot.vb_epidist","text":"Joshua W. Lambert","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/plot.vb_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot method for class — plot.vb_epidist","text":"","code":"# plot vb_epidist dengue_dist <- vb_epidist( intrinsic_epidist = epidist( disease = \"dengue\", epi_dist = \"incubation\", 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\", epi_dist = \"incubation\", 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 plot(dengue_dist, day_range = 0:10)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for class — print.epidist","title":"Print method for class — print.epidist","text":"Print method 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 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 class — print.epidist","text":"x object. header Boolean logical determining whether header (first part) print method printed. used internally plotting class. vb character string containing whether intrinsic (\"Intrinsic\") extrinsic (\"Extrinsic\") distribution vector-borne diseases. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for class — print.epidist","text":"Invisibly returns . 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 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 class — print.multi_epidist","title":"Print method for class — print.multi_epidist","text":"Print method 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 class — print.multi_epidist","text":"","code":"# S3 method for multi_epidist print(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.multi_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for class — print.multi_epidist","text":"x object. ... dots Extra arguments passed methods.","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 class — print.multi_epidist","text":"Invisibly returns . Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for class — print.vb_epidist","title":"Print method for class — print.vb_epidist","text":"Print method 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 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 class — print.vb_epidist","text":"x object. ... dots Extra arguments passed methods.","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 class — print.vb_epidist","text":"Invisibly returns . 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 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.” #> #> #> #> Distribution: gamma #> Parameters: #> shape: 1.000 #> scale: 1.000 #> #> #> #> 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 class — validate_epidist","title":"Validator for class — validate_epidist","text":"Validator 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 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 class — validate_epidist","text":"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 class — validate_epidist","text":"Invisibly returns . Called side-effects (errors invalid object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for class — validate_vb_epidist","title":"Validator for class — validate_vb_epidist","text":"Validator 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 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 class — validate_vb_epidist","text":"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 class — validate_vb_epidist","text":"Invisibly returns . Called side-effects (errors invalid object provided).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a object — vb_epidist","title":"Create a object — vb_epidist","text":" class extension class (although subclass ). used store epidemiological parameters vector-borne diseases. methods (print(), format(), plot(), generate(), cdf(), density(), quantile()) 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 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 object — vb_epidist","text":"intrinsic_epidist object. extrinsic_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 object — vb_epidist","text":" object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/vb_epidist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a object — vb_epidist","text":" 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 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-010","dir":"Changelog","previous_headings":"","what":"epiparameter 0.1.0","title":"epiparameter 0.1.0","text":"Initial release {epiparameter}, R package work epidemiological parameters distributions, contains library epidemiological parameters.","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 epidemiological parameters (parameters.json) stored internal data (inst/extdata). Distribution parameter conversion extraction functions (convert_params_to_summary_stats() & convert_summary_stats_to_params(), extract_param()). S3 classes work parameters , . classes accompanied S3 methods aid users easily work data structures. include printing, plotting, distribution functions PDF/PMF, CDF, random number generation distribution quantiles. class constructor validator. package contains utility functions. Four 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) 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, 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":""}] diff --git a/sitemap.xml b/sitemap.xml index f9ea515ca..3bad9ab97 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -39,6 +39,9 @@ https://epiverse-trace.github.io/epiparameter/news/index.html + + https://epiverse-trace.github.io/epiparameter/reference/as.function.epidist.html + https://epiverse-trace.github.io/epiparameter/reference/calc_disc_dist_quantile.html