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Distribution functionsquantile(ebola_incubation, p = 0.5) #> [1] 2.718282 generate(ebola_incubation, times = 10) -#> [1] 2.086442 2.707473 1.702436 9.560153 7.996875 2.386485 1.908604 -#> [8] 24.226173 3.856476 5.665743 +#> [1] 14.4432826 2.0297665 10.6703451 9.1135557 0.4496396 10.5164219 +#> [7] 11.8342655 2.4529662 0.5389239 2.1628564
diff --git a/articles/extract_convert.html b/articles/extract_convert.html index b786e6ee5..e50506cbd 100644 --- a/articles/extract_convert.html +++ b/articles/extract_convert.html @@ -401,7 +401,7 @@

Extraction#> Stochastic numerical optimisation used. #> Rerun function multiple times to check global optimum is found #> shape scale -#> 3.358212 1.284183

+#> 3.358187 1.284186

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.

@@ -415,7 +415,7 @@

Extraction#> Stochastic numerical optimisation used. #> Rerun function multiple times to check global optimum is found #> meanlog sdlog -#> 2.302585 3.652107 +#> 2.302585 2.646129

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
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@@ -74,7 +74,11 @@ 
Authors

           

         
         
  • 
-          
    Hugo Gruson. Contributor. 
+          
    Hugo Gruson. Contributor, reviewer. 
+          
    
+        
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+        
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    Pratik Gupte. Reviewer. 
           
    
         
    •
    diff --git a/favicon-16x16.png b/favicon-16x16.png index 85d7e3631..27839bc31 100644 Binary files a/favicon-16x16.png and b/favicon-16x16.png differ diff --git a/favicon-32x32.png b/favicon-32x32.png index 99f2b399e..74b3d9d96 100644 Binary files a/favicon-32x32.png and b/favicon-32x32.png differ diff --git a/pkgdown.yml b/pkgdown.yml index da3829598..58c7d52ee 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -6,7 +6,7 @@ articles: epiparameter: epiparameter.html extract-bias: extract-bias.html extract_convert: extract_convert.html -last_built: 2023-09-07T11:46Z +last_built: 2023-09-07T12:16Z urls: reference: https://epiverse-trace.github.io/epiparameter/reference article: https://epiverse-trace.github.io/epiparameter/articles diff --git a/reference/epidist_distribution_functions.html b/reference/epidist_distribution_functions.html index e31f270fd..acfc8bbe4 100644 --- a/reference/epidist_distribution_functions.html +++ b/reference/epidist_distribution_functions.html @@ -163,8 +163,8 @@

    Examplesstats::quantile(edist, p = 0.2) #> [1] 0.2231436 distributional::generate(edist, times = 10) -#> [1] 0.31422639 0.24454463 1.30170550 0.44205160 0.10718003 0.13056311 -#> [7] 0.04496172 0.89894096 0.24799949 1.24019094 +#> [1] 2.7914140 1.1741894 1.3286020 0.2825627 0.4140444 0.5128917 0.1931127 +#> [8] 0.0831748 0.5239166 0.1059182 vb_edist <- vb_epidist( intrinsic_epidist = epidist( @@ -212,12 +212,12 @@

    Examples#> distributional::generate(vb_edist, times = 10) #> $intrinsic -#> [1] 2.89804639 2.57037732 1.00925402 0.05434762 0.79621785 0.69836000 -#> [7] 0.21704365 3.06554786 0.63613865 0.16074288 +#> [1] 1.1349881 2.8008354 2.4924802 0.2825947 3.8515281 1.5624448 0.5885463 +#> [8] 0.6735860 1.8987479 0.1601222 #> #> $extrinsic -#> [1] 0.7749581 1.0461760 1.6857273 1.1218597 0.1025819 0.3029804 0.1886351 -#> [8] 0.6733771 0.1595303 0.1089408 +#> [1] 1.043827886 0.881601493 0.157763926 0.050841083 1.336452325 0.007527032 +#> [7] 0.490471171 3.405340406 0.871274401 0.400682147 #> diff --git a/search.json b/search.json index 3e0e41c3f..d3548bfa6 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 distribution 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. Contributions can added google sheet. 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 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":"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":""},{"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. Across site performed search. 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. database unsuitable papers kept remind maintainers papers included aids updating databse (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 distirbution), 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. minimal dataset required included epiparameter library : Name disease Type distribution Author(s) paper year publication transmission mode pathogen (.e. directly transmitted vector-borne) Whether distribution extrinsic (e.g. extrinsic incubation period). disease vector-borne NA. type distribution fitted, either distribution fit best-fit set candidate distributions Parameter distribution (e.g. shape scale case gamma, meanlog sdlog case lognormal, etc.) Mean standard deviation (equivalently variance coefficient variation) Median range two quantiles. Ideally lower quantile (q < 0.5) upper quantile (q > 0.5) ensure reliable estimation parameters Whether distribution fitted discretised, boolean (true false). Digital Object Identifier (DOI) paper Data recommended essential: Name pathogen Sample size data used fit distribution region data collected, either natioanl, continental global level Type vector Uncertainty estimated parameters summary statistics, needs provided type inference used (e.g. maximum likelihood bayesian) avoid potential misuse uncertainty (e.g. mistaking confindence interval credible interval) Additional unique identifiers paper, exampel PubMed ID (PMID) Whether distribution fitted adjusted phase bias Whether disribution used interval-censoring Whether distribution right-truncated truncation point ‘Notes’: can include general statements distribution methodology used paper. notes can accessed using package make users aware possible limitations distribution parameters may fit categories 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 methological 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 skrinking 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 subsquent 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/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 three new classes working epidemiological parameters R: : library epidemiolgical parameters : singular set epidemiolgical parameters : singular set epidemiolgical parameters vector-borne disease containing extrinsic intrinsic distribution. object contains two sets parameters, one human (intrinsic) 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. Extra arguments also available epidist() add information uncertainty citation information.","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}. class introduced enable users easily explore range parameters available. library can read R using epiparam() function. default entries library supplied. class custom printing method gives summary information included database including number distributions, number diseases, number different studies among summary metrics, well first six rows diseases, epidemiological distributions (epi_distribution) probability distribution (prob_distribution). class based (.e. inherits ) data frame, therefore subsetting manipulation can carried , including head() tail() database. epidemiological library contains multiple columns, storing different features parameter: subsetting object removes one essential columns object converted data frame. example, removing disease column causes object converted data frame. See Epiverse-TRACE blog post extending data frames technical description. see full list diseases distributions stored library use list_distributions() function. show first six rows output. details data collation library parameters can found Data Collation Synthesis Protocol vignette.","code":"epi_dist_db <- epiparam() epi_dist_db #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown> head(epi_dist_db)[, 1:4] #> disease pathogen epi_distribution author #> 1 Adenovirus Adenovirus incubation_period Lessler_etal #> 2 Chikungunya Chikungunya Virus incubation_period Rudolph_etal #> 3 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 4 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 5 COVID-19 SARS-CoV-2 incubation_period Alene_etal #> 6 COVID-19 SARS-CoV-2 incubation_period Bui_etal tail(epi_dist_db)[, 1:4] #> disease pathogen epi_distribution author #> 113 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 114 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 115 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 116 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 117 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 118 Zika Virus Disease Zika Virus incubation_period Lessler_etal colnames(epi_dist_db) #> [1] \"disease\" \"pathogen\" \"epi_distribution\" #> [4] \"author\" \"title\" \"journal\" #> [7] \"year\" \"sample_size\" \"region\" #> [10] \"transmission_mode\" \"vector\" \"extrinsic\" #> [13] \"prob_distribution\" \"inference_method\" \"mean\" #> [16] \"mean_ci_limits\" \"mean_ci\" \"sd\" #> [19] \"sd_ci_limits\" \"sd_ci\" \"quantile_2.5\" #> [22] \"quantile_5\" \"quantile_25\" \"median\" #> [25] \"median_ci_limits\" \"median_ci\" \"quantile_75\" #> [28] \"quantile_87.5\" \"quantile_95\" \"quantile_97.5\" #> [31] \"lower_range\" \"upper_range\" \"shape\" #> [34] \"shape_ci_limits\" \"shape_ci\" \"scale\" #> [37] \"scale_ci_limits\" \"scale_ci\" \"meanlog\" #> [40] \"meanlog_ci_limits\" \"meanlog_ci\" \"sdlog\" #> [43] \"sdlog_ci_limits\" \"sdlog_ci\" \"dispersion\" #> [46] \"dispersion_ci_limits\" \"dispersion_ci\" \"precision\" #> [49] \"precision_ci_limits\" \"precision_ci\" \"truncation\" #> [52] \"discretised\" \"censored\" \"right_truncated\" #> [55] \"phase_bias_adjusted\" \"notes\" \"PMID\" #> [58] \"DOI\" epi_dist_df <- epi_dist_db[colnames(epi_dist_db) != \"disease\"] #> Removing crucial column in `` returning `` head(list_distributions(epi_dist_db)) #> disease epi_distribution prob_distribution author year sample_size #> 1 Adenovirus incubation_period lnorm Lessler_etal 2009 14 #> 2 Chikungunya incubation_period lnorm Rudolph_etal 2014 21 #> 3 COVID-19 incubation_period Alene_etal 2021 1453 #> 4 COVID-19 incubation_period weibull Bui_etal 2020 19 #> 5 COVID-19 incubation_period Elias_etal 2021 28675 #> 6 COVID-19 incubation_period lnorm Lauer_etal 2020 181"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"single-set-of-epidemiolgical-parameters","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Single set of epidemiolgical parameters","title":"Getting Started with {epiparameter}","text":"second class introduced {epiparameter} package class. holds single set epidemiological parameters. object can converted one rows object can created manually. First show conversion → . uses as_epidist() function. object also custom printing method shows disease, pathogen (known), epidemiological distribution, citation study parameters probability distribution parameter distribution (available). opposite conversion can also achieved using as_epiparam(). two alternatives reading objects subsetting . Extract directly library epidist_db(). Create manually constructor function. epidist_db() allows direct subsetting library returns single set epidemiological parameters. Additionally using entries {epiparameter} library, objects can manually created. may especially useful new parameter estimates become available yet incorporated library.","code":"# find entry for COVID-19 epi_dist_covid <- epi_dist_db[epi_dist_db$disease == \"COVID-19\", ] # find entry for COVID-19 incubation period epi_dist_covid_incub <- epi_dist_covid[epi_dist_covid$epi_distribution == \"incubation_period\", ] # nolint # select one of the COVID-19 incubation period covid_incub <- epi_dist_covid_incub[10, ] # convert epiparam entry to epidist covid_incub <- as_epidist(covid_incub) #> Using Linton, etal (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 #> . #> To retrieve the citation use the 'get_citation' function covid_incub #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton, etal (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 as_epiparam(covid_incub) #> Epiparam object #> Number of distributions in library: 1 #> Number of diseases: 1 #> Number of delay distributions: 1 #> Number of offspring distributions: 0 #> Number of studies in library: 1 #> #> disease epi_distribution prob_distribution #> 1 COVID-19 incubation_period lnorm #> <0 more rows & 55 more cols not shown> epidist_db( disease = \"COVID-19\", epi_dist = \"incubation_period\", author = \"Bui_etal\" ) #> Using Bui, etal (2020). \"Estimation of the incubation period of COVID-19 in #> Vietnam.\" _PLoS One_. doi:10.1371/journal.pone.0243889 #> . #> To retrieve the citation use the 'get_citation' function #> Numerical approximation used, results may be unreliable. #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Bui, etal (2020). \"Estimation of the incubation period of COVID-19 in #> Vietnam.\" _PLoS One_. doi:10.1371/journal.pone.0243889 #> . #> Distribution: weibull #> Parameters: #> shape: 2.217 #> scale: 7.226 ebola_incubation <- 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"},{"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":"adding-library-entries","dir":"Articles","previous_headings":"","what":"Adding library entries","title":"Getting Started with {epiparameter}","text":"set epidemiological parameter inferred known user yet incorporated {epiparameter} database, parameters can manually added library. add entries library provide function bind data objects: bind_epiparam(). function provided multiple data types (classes) can bound existing object (subclass ). bind_epiparam() can bind , (including ), lists. Note adds parameters library ( object) environment, save database file package. binding columns use either tibble::add_column() dplyr::bind_cols(). Using cbind() unclass object (.e. convert ). Note dplyr::bind_cols() print message returned, case.","code":"bind_epiparam(epiparam = epi_dist_db, epi_obj = ebola_incubation) #> Epiparam object #> Number of distributions in library: 119 #> Number of diseases: 24 #> Number of delay distributions: 96 #> Number of offspring distributions: 10 #> Number of studies in library: 58 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <113 more rows & 55 more cols not shown> bind_epiparam(epiparam = epi_dist_db, epi_obj = as_epiparam(ebola_incubation)) #> Epiparam object #> Number of distributions in library: 119 #> Number of diseases: 24 #> Number of delay distributions: 96 #> Number of offspring distributions: 10 #> Number of studies in library: 58 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <113 more rows & 55 more cols not shown>"},{"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":"density(ebola_incubation, at = 0.5) #> [1] 0.1902978 cdf(ebola_incubation, q = 0.5) #> [1] 0.04521373 quantile(ebola_incubation, p = 0.5) #> [1] 2.718282 generate(ebola_incubation, times = 10) #> [1] 2.086442 2.707473 1.702436 9.560153 7.996875 2.386485 1.908604 #> [8] 24.226173 3.856476 5.665743"},{"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":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"contributing-to-epiparameter","dir":"Articles","previous_headings":"","what":"Contributing to {epiparameter}","title":"Getting Started with {epiparameter}","text":"library epidemiological parameters living database, new studies published hope incorporate . Due large time requirement searching recording parameters database welcome others add parameters contributing spreadsheet. incorporated database package maintainers. See Data Collation Synthesis Protocol vignette information contributing library epidemiological parameters.","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. # 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 #> 3.358212 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 3.652107 # 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.","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: library class, underneath data frame. entry library can converted object used. object can plotted.","code":"library(epiparameter) eparams <- epiparam() eparams #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown> influenza_incubation <- as_epidist(eparams[12, ]) #> Using Linton, etal (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 #> . #> To retrieve the citation use the 'get_citation' function influenza_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton, etal (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 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_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert to — as_epidist","title":"Convert to — as_epidist","text":"Convert entries (rows) object one list several objects. Epidemiological distributions parameters can converted database entries (.e. rows ) objects order use distribution functions (see ?epidist_distribution_functions) methods class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert to — as_epidist","text":"","code":"as_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert to — as_epidist","text":"x object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert to — as_epidist","text":" object list objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert to — as_epidist","text":"","code":"# \\donttest{ eparam <- epiparam() as_epidist(eparam[1, ]) #> Using Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> . #> To retrieve the citation use the 'get_citation' function #> Stochastic numerical optimisation used. #> Rerun function multiple times to check global optimum is found #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> . #> Distribution: lnorm #> Parameters: #> meanlog: 1.720 #> sdlog: 0.225 # }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert an object to an object — as_epiparam","title":"Convert an object to an object — as_epiparam","text":"Convert object object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert an object to an object — as_epiparam","text":"","code":"as_epiparam(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert an object to an object — as_epiparam","text":"x object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert an object to an object — as_epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert an object to an object — as_epiparam","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 as_epiparam(edist) #> Epiparam object #> Number of distributions in library: 1 #> Number of diseases: 1 #> Number of delay distributions: 1 #> Number of offspring distributions: 0 #> Number of studies in library: 1 #> #> disease epi_distribution prob_distribution #> 1 ebola incubation_period lnorm #> <0 more rows & 55 more cols not shown>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Bind an epi object to an object — bind_epiparam","title":"Bind an epi object to an object — bind_epiparam","text":"Bind epi data class epiparameter (, , ) data frame object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bind an epi object to an object — bind_epiparam","text":"","code":"bind_epiparam(epiparam, epi_obj)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bind an epi object to an object — bind_epiparam","text":"epiparam object. epi_obj Either , , list objects. can also data frame long columns conform columns object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bind an epi object to an object — bind_epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bind an epi object to an object — bind_epiparam","text":" class holds library epidemiological parameters stored epiparameter R package can manipulated. bind_epiparam() function allows users add entries library binding bottom existing object loaded R. returned bind_epiparam() contains matching columns input objects. Therefore, one input objects contains extra columns present input object missing returned object. also applies whether binding objects. binding objects missing data fields given default value binding.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bind an epi object to an object — bind_epiparam","text":"","code":"eparam <- epiparam() 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 bind_epiparam(eparam, edist) #> Epiparam object #> Number of distributions in library: 119 #> Number of diseases: 24 #> Number of delay distributions: 96 #> Number of offspring distributions: 10 #> Number of studies in library: 58 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <113 more rows & 55 more cols not shown>"},{"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, summary_stats, sample_size = NA)"},{"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). 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(q_2.5 = 0.2, q_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/cash-set-.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Set accessor for epiparam class — $<-.epiparam","title":"Set accessor for epiparam class — $<-.epiparam","text":"Set accessor epiparam class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/cash-set-.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set accessor for epiparam class — $<-.epiparam","text":"","code":"# S3 method for epiparam $(x, name) <- value"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/cash-set-.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set accessor for epiparam class — $<-.epiparam","text":"x epiparam object name literal character string name (possibly backtick quoted). extraction, normally (see ‘Environments’) partially matched names object. value typically array-like R object similar class x.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/cash-set-.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set accessor for epiparam class — $<-.epiparam","text":"epiparam object data.frame","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the optimisation of distribution parameters has converged to\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_epidist_name.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the names of epidemiological distributions — clean_epidist_name","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"Standardise names epidemiological distributions","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"","code":"clean_epidist_name(epi_dist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"epi_dist character string name distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"","code":"clean_epidist_name(\"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.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 = NA_character_, 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 character string surname first author. can underscore separated second author, underscore separated \"etal\" two authors. 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 = \"Smith_etal\", year = 2002, title = \"COVID-19 incubation period\", journal = \"Epi Journal\", DOI = \"10.19832/j.1366-9516.2012.09147.x\" ) #> Using Smith, etal (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, etal (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_, dispersion = NA_real_, dispersion_ci_limits = c(NA_real_, NA_real_), dispersion_ci = NA_real_, lower_range = NA_real_, upper_range = NA_real_, quantiles = c(q_2.5 = NA_real_, q_5 = NA_real_, q_25 = NA_real_, q_50 = NA_real_, q_75 = NA_real_, q_95 = NA_real_, q_97.5 = 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. dispersion numeric dispersion parameter distribution. dispersion_ci_limits numeric vector length two confidence interval around dispersion. dispersion_ci numeric specifying confidence interval width dispersion parameter. 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) #> $centre_spread #> $centre_spread$mean #> [1] 5 #> #> $centre_spread$mean_ci_limits #> [1] NA NA #> #> $centre_spread$mean_ci #> [1] NA #> #> $centre_spread$sd #> [1] 2 #> #> $centre_spread$sd_ci_limits #> [1] NA NA #> #> $centre_spread$sd_ci #> [1] NA #> #> $centre_spread$median #> [1] NA #> #> $centre_spread$median_ci_limits #> [1] NA NA #> #> $centre_spread$median_ci #> [1] NA #> #> #> $quantiles #> q_2.5 q_5 q_25 q_50 q_75 q_95 q_97.5 #> NA NA NA NA NA NA NA #> #> $range #> $range$lower_range #> [1] NA #> #> $range$upper_range #> [1] NA #> #> #> $dispersion #> $dispersion$dispersion #> [1] NA #> #> $dispersion$dispersion_ci_limits #> [1] NA NA #> #> $dispersion$dispersion_ci #> [1] 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 ) #> $centre_spread #> $centre_spread$mean #> [1] 4 #> #> $centre_spread$mean_ci_limits #> [1] 2.1 5.7 #> #> $centre_spread$mean_ci #> [1] 95 #> #> $centre_spread$sd #> [1] 0.7 #> #> $centre_spread$sd_ci_limits #> [1] 0.3 1.1 #> #> $centre_spread$sd_ci #> [1] 95 #> #> $centre_spread$median #> [1] NA #> #> $centre_spread$median_ci_limits #> [1] NA NA #> #> $centre_spread$median_ci #> [1] NA #> #> #> $quantiles #> q_2.5 q_5 q_25 q_50 q_75 q_95 q_97.5 #> NA NA NA NA NA NA NA #> #> $range #> $range$lower_range #> [1] NA #> #> $range$upper_range #> [1] NA #> #> #> $dispersion #> $dispersion$dispersion #> [1] NA #> #> $dispersion$dispersion_ci_limits #> [1] NA NA #> #> $dispersion$dispersion_ci #> [1] NA #> #> # median and range create_epidist_summary_stats( median = 5, lower_range = 1, upper_range = 13 ) #> $centre_spread #> $centre_spread$mean #> [1] NA #> #> $centre_spread$mean_ci_limits #> [1] NA NA #> #> $centre_spread$mean_ci #> [1] NA #> #> $centre_spread$sd #> [1] NA #> #> $centre_spread$sd_ci_limits #> [1] NA NA #> #> $centre_spread$sd_ci #> [1] NA #> #> $centre_spread$median #> [1] 5 #> #> $centre_spread$median_ci_limits #> [1] NA NA #> #> $centre_spread$median_ci #> [1] NA #> #> #> $quantiles #> q_2.5 q_5 q_25 q_50 q_75 q_95 q_97.5 #> NA NA NA NA NA NA NA #> #> $range #> $range$lower_range #> [1] 1 #> #> $range$upper_range #> [1] 13 #> #> #> $dispersion #> $dispersion$dispersion #> [1] NA #> #> $dispersion$dispersion_ci_limits #> [1] NA NA #> #> $dispersion$dispersion_ci #> [1] NA #> #>"},{"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/df_reconstruct.html","id":null,"dir":"Reference","previous_headings":"","what":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":"Transplant attributes one input () input (x)","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/df_reconstruct.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":"","code":"df_reconstruct(x, to)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/df_reconstruct.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":"x data.frame subclass data.frame (e.g. ). reference object, case object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/df_reconstruct.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":" object.","code":""},{"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, ...) # 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 epiparam() as_epidist(). 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 wiht 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 'mealog' '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 = \"Smith_etal\", 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, etal (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 an object(s) directly from the epiparameter library\n(database) — epidist_db","title":"Create an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"Extract object(s) directly library epidemiological parameters. bypasses need read object convert object. 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 an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"","code":"epidist_db( disease, epi_dist = c(\"incubation_period\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\", \"generation_time\", \"offspring_distribution\"), 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 an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"disease character string specifying disease. epi_dist character string specifying epidemiological distribution. author character string specifying author study reporting distribution. subset Either NULL valid R expressions evaluates logicals subset rows , function can applied directly object. argument allows general subsetting can combined subsetting done disease epidist arguments (author specified). left NULL (default) subsetting carried . expression specified without using data object name (e.g. df$var) instead just var supplied. words, argument works subset argument subset(). similar using 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 an 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 an 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 &.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"","code":"epidist_db(disease = \"influenza\", epi_dist = \"serial_interval\") #> Using Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> To retrieve the citation use the 'get_citation' function #> Disease: Influenza #> Pathogen: Influenza-A-H1N1Pdm #> Epi Distribution: serial interval #> Study: Ghani, etal (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 # comparison between using `epidist_db()` and `epiparam()` with # `as_epidist()` # load influenza serial interval from database edist <- epidist_db(disease = \"influenza\", epi_dist = \"serial_interval\") #> Using Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> To retrieve the citation use the 'get_citation' function # load database of serial intervals eparam <- epiparam(epi_dist = \"serial_interval\") # subset database to only influenza entries eparam <- eparam[clean_disease(eparam$disease) == \"influenza\", ] # convert to `epidist` edist2 <- as_epidist(eparam) #> Using Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> To retrieve the citation use the 'get_citation' function # check the two methods produce the same `epidist` object identical(edist, edist2) #> [1] TRUE # example using custom subsetting eparam <- epidist_db( disease = \"SARS\", epi_dist = \"offspring_distribution\", subset = sample_size > 40 ) #> Using Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> To retrieve the citation use the 'get_citation' function # example using functional subsetting eparam <- epidist_db( disease = \"COVID-19\", epi_dist = \"incubation_period\", subset = is_parameterised ) #> Returning 2 results that match the criteria (2 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 list(author = list(list(given = NULL, family = \"Lloyd-Smith\", role = NULL, email = NULL, comment = NULL), list(given = NULL, family = \"etal\", role = NULL, email = NULL, comment = NULL)), year = \"2005\", title = \"Superspreading and the effect of individual variation on disease emergence\", journal = \"Nature\", doi = \"10.1038/nature04153\", pmid = \"16292310\"). #> 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, ...) # 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 . 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] 0.31422639 0.24454463 1.30170550 0.44205160 0.10718003 0.13056311 #> [7] 0.04496172 0.89894096 0.24799949 1.24019094 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] 2.89804639 2.57037732 1.00925402 0.05434762 0.79621785 0.69836000 #> [7] 0.21704365 3.06554786 0.63613865 0.16074288 #> #> $extrinsic #> [1] 0.7749581 1.0461760 1.6857273 1.1218597 0.1025819 0.3029804 0.1886351 #> [8] 0.6733771 0.1595303 0.1089408 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an object — epiparam","title":"Create an object — epiparam","text":" class holds information epidemiological distribution estimated parameters well information metadata. library epidemiological parameters compiled primary literature sources. object can used compare availability distribution certain disease pathogen, refine , example, region sample size. Additionally, class can subset converted objects used epidemiological analysis delay distribution offspring distribution required. epiparam() function reads library epidemiological parameters {epiparameter} memory stores object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an object — epiparam","text":"","code":"epiparam( epi_dist = c(\"all\", \"incubation_period\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\", \"generation_time\", \"offspring_distribution\") )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an object — epiparam","text":"epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an object — epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an object — epiparam","text":" object certain protected fields, thus one protected fields removed subsetting columns error returned. subsetting checks carried validate_epiparam(). Data can added objects using bind_epiparam(), can add information , , , lists objects, data frames correct columns existing object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an object — epiparam","text":"","code":"# the object can be made without arguments eparam <- epiparam() # specifying incubation periods incub_eparam <- epiparam(\"incubation\") # subset by disease influenza_dists <- eparam[eparam$disease == \"influenza\", ]"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the object is valid — epiparam_can_reconstruct","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"wrapper validate_epiparam() tryCatch() order error input object invalid returns TRUE FALSE object valid. object valid can \"reconstructed\" downgraded data.frame.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"","code":"epiparam_can_reconstruct(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"x data.frame subclass data.frame (e.g. ).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":null,"dir":"Reference","previous_headings":"","what":"Decide whether object can be reconstructed from input — epiparam_reconstruct","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":"Uses epiparam_can_reconstruct() determine whether data input can reconstructed valid object. can , returned data frame.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":"","code":"epiparam_reconstruct(x, to)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":"x data.frame subclass data.frame (e.g. ). reference object, case object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":" object (input valid) data.frame.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the parameters of a parametric probability distribution from\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 #> 5.339552 1.995358"},{"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.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Format method for class — format.epiparam","title":"Format method for class — format.epiparam","text":"Format method class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format method for class — format.epiparam","text":"","code":"# S3 method for epiparam format(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format method for class — format.epiparam","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for class — format.epiparam","text":"Invisibly returns . Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format method for class — format.epiparam","text":"","code":"x <- epiparam() format(x) #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown>"},{"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( disease = \"ebola\", epi_dist = \"incubation_period\", prob_distribution = \"gamma\", prob_distribution_params = c(shape = 1, scale = 1) ), extrinsic = 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 objects — get_citation","title":"Extract citation information from or objects — get_citation","text":"Extract citation information 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 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 objects — get_citation","text":"x object. ... Extra arguments passed method.","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 objects — get_citation","text":"single character string list character string citations. Length list output equal number rows 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 objects — get_citation","text":"","code":"# example with epidist eparam <- epiparam() edist <- as_epidist(eparam[12, ]) #> Using Linton, etal (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 #> . #> To retrieve the citation use the 'get_citation' function get_citation(edist) #> Linton, etal (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 #> . # example with epiparam eparam <- epiparam() get_citation(eparam) #> [[1]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> . #> #> [[2]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[3]] #> Linton, etal (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 #> . #> #> [[4]] #> Linton, etal (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 #> . #> #> [[5]] #> Alene, etal (2021). “Serial interval and incubation period of COVID-19: #> a systematic review and meta-analysis.” _BMC Infectious Diseases_. #> doi:10.1186/s12879-021-05950-x #> . #> #> [[6]] #> Bui, etal (2020). “Estimation of the incubation period of COVID-19 in #> Vietnam.” _PLoS One_. doi:10.1371/journal.pone.0243889 #> . #> #> [[7]] #> Elias, etal (2021). “The incubation period of COVID-19: A #> meta-analysis.” _International Journal of Infectious Diseases_. #> doi:10.1016/j.ijid.2021.01.069 #> . #> #> [[8]] #> Lauer, etal (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 #> . #> #> [[9]] #> Lauer, etal (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 #> . #> #> [[10]] #> Lauer, etal (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 #> . #> #> [[11]] #> Lauer, etal (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 #> . #> #> [[12]] #> Linton, etal (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 #> . #> #> [[13]] #> Linton, etal (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 #> . #> #> [[14]] #> Linton, etal (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 #> . #> #> [[15]] #> McAloon, etal (2020). “Incubation period of COVID-19: a rapid #> systematic review and meta-analysis of observational research.” _BMJ #> Open_. doi:10.1136/bmjopen-2020-039652 #> . #> #> [[16]] #> McAloon, etal (2020). “Incubation period of COVID-19: a rapid #> systematic review and meta-analysis of observational research.” _BMJ #> Open_. doi:10.1136/bmjopen-2020-039652 #> . #> #> [[17]] #> Men, etal (2020). “Estimate the incubation period of coronavirus 2019 #> (COVID-19).” _medRxiv_. doi:10.1101/2020.02.24.20027474 #> . #> #> [[18]] #> Rai, etal (2022). “Incubation period for COVID-19: a systematic review #> and meta-analysis.” _Zeitschrift fur Gesundheitswissenschaften_. #> doi:10.1007/s10389-021-01478-1 #> . #> #> [[19]] #> Linton, etal (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 #> . #> #> [[20]] #> Linton, etal (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 #> . #> #> [[21]] #> Linton, etal (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 #> . #> #> [[22]] #> Linton, etal (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 #> . #> #> [[23]] #> Linton, etal (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 #> . #> #> [[24]] #> Linton, etal (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 #> . #> #> [[25]] #> Alene, etal (2021). “Serial interval and incubation period of COVID-19: #> a systematic review and meta-analysis.” _BMC Infectious Diseases_. #> doi:10.1186/s12879-021-05950-x #> . #> #> [[26]] #> Chan, Johansson (2012). “The Incubation Periods of Dengue Viruses.” #> _PLoS One_. doi:10.1371/journal.pone.0050972 #> . #> #> [[27]] #> Chan, Johansson (2012). “The Incubation Periods of Dengue Viruses.” #> _PLoS One_. doi:10.1371/journal.pone.0050972 #> . #> #> [[28]] #> Chan, Johansson (2012). “The Incubation Periods of Dengue Viruses.” #> _PLoS One_. doi:10.1371/journal.pone.0050972 #> . #> #> [[29]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[30]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[31]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[32]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[33]] #> Eichner, etal (2011). “Incubation period of ebola hemorrhagic virus #> subtype zaire.” _Osong Public Health and Research Perspectives_. #> doi:10.1016/j.phrp.2011.04.001 #> . #> #> [[34]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414993 #> . #> #> [[35]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414994 #> . #> #> [[36]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414995 #> . #> #> [[37]] #> WHO, Ebola, ResponseTeam (2015). “West African Ebola Epidemic after One #> Year — Slowing but Not Yet under Control.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[38]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[39]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[40]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[41]] #> Barry, etal (2018). “Outbreak of Ebola virus disease in the Democratic #> Republic of the Congo, April–May, 2018: an epidemiological study.” _The #> Lancet_. doi:10.1016/S0140-6736(18)31387-4 #> . #> #> [[42]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[43]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[44]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[45]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[46]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[47]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[48]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[49]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> . #> #> [[50]] #> Lessler, etal (2009). “Outbreak of 2009 Pandemic Influenza A (H1N1) at #> a New York City School.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa0906089 . #> #> [[51]] #> Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> #> [[52]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-9 #> . #> #> [[53]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-10 #> . #> #> [[54]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-11 #> . #> #> [[55]] #> Lessler, etal (2009). “Outbreak of 2009 Pandemic Influenza A (H1N1) at #> a New York City School.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa0906089 . #> #> [[56]] #> Nishiura, Inaba (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 #> . #> #> [[57]] #> Nishiura, Inaba (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 #> . #> #> [[58]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[59]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[60]] #> Tuite, etal (2010). “Estimated epidemiologic parameters and morbidity #> associated with pandemic H1N1 influenza.” _Canadian Medical Association #> Journal_. doi:10.1503/cmaj.091807 #> . #> #> [[61]] #> Virlogeux, etal (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 #> . #> #> [[62]] #> Virlogeux, etal (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 #> . #> #> [[63]] #> Virlogeux, etal (2016). “Association between the Severity of Influenza #> A(H7N9) Virus Infections and Length of the Incubation Period.” _PLoS #> One_. doi:10.1371/journal.pone.0148506 #> . #> #> [[64]] #> Virlogeux, etal (2016). “Association between the Severity of Influenza #> A(H7N9) Virus Infections and Length of the Incubation Period.” _PLoS #> One_. doi:10.1371/journal.pone.0148506 #> . #> #> [[65]] #> Virlogeux, etal (2016). “Association between the Severity of Influenza #> A(H7N9) Virus Infections and Length of the Incubation Period.” _PLoS #> One_. doi:10.1371/journal.pone.0148506 #> . #> #> [[66]] #> Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> #> [[67]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[68]] #> Pavlin (2014). “Calculation of incubation period and serial interval #> from multiple outbreaks of Marburg virus disease.” _BMC Research #> Notes_. doi:10.1186/1756-0500-7-906 #> . #> #> [[69]] #> Pavlin (2014). “Calculation of incubation period and serial interval #> from multiple outbreaks of Marburg virus disease.” _BMC Research #> Notes_. doi:10.1186/1756-0500-7-906 #> . #> #> [[70]] #> Colebunders (2007). “Marburg hemorrhagic fever in Durba and Watsa, #> Democratic Republic of the Congo: clinical documentation, features of #> illness, and treatment.” _The Journal of Infectious Diseases_. #> doi:10.1086/520543 . #> #> [[71]] #> Ajelli, Merler (2012). “Transmission Potential and Design of Adequate #> Control Measures for Marburg Hemorrhagic Fever.” _PLoS One_. #> doi:10.1371/journal.pone.0050948 #> . #> #> [[72]] #> Pavlin (2014). “Calculation of incubation period and serial interval #> from multiple outbreaks of Marburg virus disease.” _BMC Research #> Notes_. doi:10.1186/1756-0500-7-906 #> . #> #> [[73]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-12 #> . #> #> [[74]] #> Assiri, etal (2013). “Hospital Outbreak of Middle East Respiratory #> Syndrome Coronavirus.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa1306742 . #> #> [[75]] #> Cowling, etal (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 #> . #> #> [[76]] #> Assiri, etal 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of #> MERS-CoV outbreak in South Korea, May to June 2016.” #> _Eurosurveillance_. doi:10.2807/1560-7917.es2015.20.25.21163 #> . #> #> [[82]] #> Charniga, etal (2022). “Estimating the incubation period of monkeypox #> virus during the 2022 multi-national outbreak.” _medRxiv_. #> doi:10.1101/2022.06.22.22276713 #> . #> #> [[83]] #> Guzetta, etal (2022). “Early Estimates of Monkeypox Incubation Period, #> Generation Time, and Reproduction Number, Italy, May-June 2022.” #> _Emerging Infectious Diseases_. doi:10.3201/eid2810.221126 #> . #> #> [[84]] #> Madewell, etal (2022). “Serial interval and incubation period estimates #> of monkeypox virus infection in 12 U.S. jurisdictions, May – August #> 2022.” _medRxiv_. doi:10.1101/2022.10.26.22281516 #> . #> #> [[85]] #> Madewell, etal (2022). “Serial interval and incubation period estimates #> of monkeypox virus infection in 12 U.S. jurisdictions, May – August #> 2023.” _medRxiv_. doi:10.1101/2022.10.26.22281517 #> . #> #> [[86]] #> Miura, etal 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[[97]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac105 . #> #> [[98]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac106 . #> #> [[99]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-13 #> . #> #> [[100]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[101]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-15 #> . #> #> [[102]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[103]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-14 #> . #> #> [[104]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[105]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[106]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> . #> #> [[107]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[108]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[109]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[110]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[111]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[112]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[113]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[114]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[115]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[116]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[117]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[118]] #> Lessler, etal (2016). “Times to key events in Zika virus infection and #> implications for blood donation: a systematic review.” _Bulletin of the #> World Health Organization_. doi:10.2471/BLT.16.174540 #> . #>"},{"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 \"q_\" followed value. 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(q_5 = 1, q_95 = 10)) # 95th interval get_percentiles(c(q_2.5 = 1, q_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/head.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"head() and tail() methods for class — head.epiparam","title":"head() and tail() methods for class — head.epiparam","text":"head() tail() methods class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"head() and tail() methods for class — head.epiparam","text":"","code":"# S3 method for epiparam head(x, ...) # S3 method for epiparam tail(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"head() and tail() methods for class — head.epiparam","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"head() and tail() methods for class — head.epiparam","text":"Data frame","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"head() and tail() methods for class — head.epiparam","text":"","code":"head(epiparam()) #> disease pathogen epi_distribution author #> 1 Adenovirus Adenovirus incubation_period Lessler_etal #> 2 Chikungunya Chikungunya Virus incubation_period Rudolph_etal #> 3 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 4 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 5 COVID-19 SARS-CoV-2 incubation_period Alene_etal #> 6 COVID-19 SARS-CoV-2 incubation_period Bui_etal #> title #> 1 Incubation periods of acute respiratory viral infections: a systematic review #> 2 Incubation periods of mosquito-borne viral infections: a systematic review #> 3 Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data #> 4 Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data #> 5 Serial interval and incubation period of COVID-19: a systematic review and meta-analysis #> 6 Estimation of the incubation period of COVID-19 in Vietnam #> journal year sample_size #> 1 The Lancet Infectious Diseases 2009 14 #> 2 The American Journal of Tropical Medicine and Hygiene 2014 21 #> 3 Journal of Clinical Medicine 2020 39 #> 4 Journal of Clinical Medicine 2020 39 #> 5 BMC Infectious Diseases 2021 1453 #> 6 PLoS One 2020 19 #> region transmission_mode vector extrinsic #> 1 USA experimental FALSE #> 2 Mixed vector_borne Aedes albopictus FALSE #> 3 China natural_human_to_human FALSE #> 4 China natural_human_to_human FALSE #> 5 Mixed natural_natural_human_to_human FALSE #> 6 Vietnam natural_natural_human_to_human FALSE #> prob_distribution inference_method mean mean_ci_limits mean_ci sd #> 1 lnorm mle NA NA, NA NA NA #> 2 lnorm mle NA NA, NA NA NA #> 3 weibull bayesian 8.9 7.3, 10.4 95 5.70 #> 4 lnorm bayesian 13.0 8.7, 20.9 95 12.70 #> 5 6.5 5.9, 7.1 95 NA #> 6 weibull bayesian 6.4 4.89, 8.50 95 3.05 #> sd_ci_limits sd_ci quantile_2.5 quantile_5 quantile_25 median #> 1 NA, NA NA NA NA 4.8 5.6 #> 2 NA, NA NA NA NA 2.9 3.0 #> 3 4.3, 7.8 95 NA 1.7 NA 8.0 #> 4 6.4, 26.0 95 NA 2.5 NA 9.1 #> 5 NA, NA NA NA NA NA NA #> 6 3.05, 5.30 95 1.35 1.9 NA 6.1 #> median_ci_limits median_ci quantile_75 quantile_87.5 quantile_95 #> 1 4.8, 6.3 95 6.5 NA NA #> 2 0.5, 3.1 95 3.0 NA NA #> 3 6.2, 9.8 95 NA NA 18.8 #> 4 6.7, 13.7 95 NA NA 33.1 #> 5 NA, NA NA NA NA NA #> 6 NA, NA NA NA NA 11.9 #> quantile_97.5 lower_range upper_range shape shape_ci_limits shape_ci scale #> 1 NA NA NA NA NA, NA NA NA #> 2 NA NA NA NA NA, NA NA NA #> 3 NA NA NA NA NA, NA NA NA #> 4 NA NA NA NA NA, NA NA NA #> 5 NA NA NA NA NA, NA NA NA #> 6 13.04 NA NA NA NA, NA NA NA #> scale_ci_limits scale_ci meanlog meanlog_ci_limits meanlog_ci sdlog #> 1 NA, NA NA NA NA, NA NA NA #> 2 NA, NA NA NA NA, NA NA NA #> 3 NA, NA NA NA NA, NA NA NA #> 4 NA, NA NA NA NA, NA NA NA #> 5 NA, NA NA NA NA, NA NA NA #> 6 NA, NA NA NA NA, NA NA NA #> sdlog_ci_limits sdlog_ci dispersion dispersion_ci_limits dispersion_ci #> 1 NA, NA NA 1.26 1.13, 1.38 95 #> 2 NA, NA NA 1.04 1.04, 1.08 95 #> 3 NA, NA NA NA NA, NA NA #> 4 NA, NA NA NA NA, NA NA #> 5 NA, NA NA NA NA, NA NA #> 6 NA, NA NA NA NA, NA NA #> precision precision_ci_limits precision_ci truncation discretised censored #> 1 NA NA, NA NA NA FALSE TRUE #> 2 NA NA, NA NA NA FALSE TRUE #> 3 NA NA, NA NA NA FALSE TRUE #> 4 NA NA, NA NA NA FALSE TRUE #> 5 NA NA, NA NA NA FALSE FALSE #> 6 NA NA, NA NA NA FALSE TRUE #> right_truncated phase_bias_adjusted #> 1 FALSE FALSE #> 2 FALSE FALSE #> 3 FALSE FALSE #> 4 TRUE TRUE #> 5 FALSE FALSE #> 6 FALSE FALSE #> notes #> 1 Analysis on data from Commission on Acute Respiratory Disease. Experimental transmission of minor respiratory illness to human volunteers by filter-passing agents. I. Demonstration of two types of illness characterized by long and short incubation periods and diff erent clinical features. J Clin Invest 1947; 26: 957–82. #> 2 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets #> 3 This method does not apply right-truncation, but does compare the gamma, weibull and lognormal distributions. #> 4 This method applies right-truncation but only fits a lognormal distribution. #> 5 This estimated mean incubation period is from a meta-analysis of 14 other incubation period estimates. Only the mean is reported and a distribution cannot be specified as the meta-mean is estimated from a random-effects model. #> 6 No additional notes #> PMID DOI #> 1 19393959 10.1016/S1473-3099(09)70069-6 #> 2 24639305 10.4269/ajtmh.13-0403 #> 3 32079150 10.3390/jcm9020538 #> 4 32079150 10.3390/jcm9020538 #> 5 33706702 10.1186/s12879-021-05950-x #> 6 33362233 10.1371/journal.pone.0243889 tail(epiparam()) #> disease pathogen epi_distribution author #> 113 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 114 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 115 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 116 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 117 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 118 Zika Virus Disease Zika Virus incubation_period Lessler_etal #> title #> 113 Incubation periods of mosquito-borne viral infections: a systematic review #> 114 Incubation periods of mosquito-borne viral infections: a systematic review #> 115 Incubation periods of mosquito-borne viral infections: a systematic review #> 116 Incubation periods of mosquito-borne viral infections: a systematic review #> 117 Incubation periods of mosquito-borne viral infections: a systematic review #> 118 Times to key events in Zika virus infection and implications for blood donation: a systematic review #> journal year sample_size #> 113 The American Journal of Tropical Medicine and Hygiene 2014 18 #> 114 The American Journal of Tropical Medicine and Hygiene 2014 8 #> 115 The American Journal of Tropical Medicine and Hygiene 2014 6 #> 116 The American Journal of Tropical Medicine and Hygiene 2014 91 #> 117 The American Journal of Tropical Medicine and Hygiene 2014 80 #> 118 Bulletin of the World Health Organization 2016 25 #> region transmission_mode vector extrinsic #> 113 Mixed multiple FALSE #> 114 Mixed vector_borne mosquito FALSE #> 115 Mixed organ_transplant FALSE #> 116 Mixed multiple FALSE #> 117 Mixed vector_borne mosquito FALSE #> 118 Mixed vector_borne Aedes aegypti and Aedes albopictus FALSE #> prob_distribution inference_method mean mean_ci_limits mean_ci sd #> 113 lnorm mle NA NA, NA NA NA #> 114 lnorm mle NA NA, NA NA NA #> 115 lnorm mle NA NA, NA NA NA #> 116 lnorm mle NA NA, NA NA NA #> 117 lnorm mle NA NA, NA NA NA #> 118 lnorm bayesian NA NA, NA NA NA #> sd_ci_limits sd_ci quantile_2.5 quantile_5 quantile_25 median #> 113 NA, NA NA NA 1.0 1.7 2.6 #> 114 NA, NA NA NA NA 2.8 2.9 #> 115 NA, NA NA NA NA 8.7 10.8 #> 116 NA, NA NA NA 1.9 3.2 4.4 #> 117 NA, NA NA NA 1.9 3.1 4.4 #> 118 NA, NA NA NA 3.2 4.6 5.9 #> median_ci_limits median_ci quantile_75 quantile_87.5 quantile_95 #> 113 1.6, 3.5 95 3.8 NA 7.0 #> 114 0.5, 3.1 95 3.0 NA NA #> 115 8.4, 14.2 95 13.3 NA NA #> 116 4, 5 95 6.3 NA 10.3 #> 117 3.9, 5.0 95 6.2 NA 10.3 #> 118 4.4, 7.6 95 7.6 NA 11.2 #> quantile_97.5 lower_range upper_range shape shape_ci_limits shape_ci scale #> 113 NA NA NA NA NA, NA NA NA #> 114 NA NA NA NA NA, NA NA NA #> 115 NA NA NA NA NA, NA NA NA #> 116 NA NA NA NA NA, NA NA NA #> 117 NA NA NA NA NA, NA NA NA #> 118 NA NA NA NA NA, NA NA NA #> scale_ci_limits scale_ci meanlog meanlog_ci_limits meanlog_ci sdlog #> 113 NA, NA NA NA NA, NA NA NA #> 114 NA, NA NA NA NA, NA NA NA #> 115 NA, NA NA NA NA, NA NA NA #> 116 NA, NA NA NA NA, NA NA NA #> 117 NA, NA NA NA NA, NA NA NA #> 118 NA, NA NA NA NA, NA NA NA #> sdlog_ci_limits sdlog_ci dispersion dispersion_ci_limits dispersion_ci #> 113 NA, NA NA 1.82 1.27, 2.67 95 #> 114 NA, NA NA 1.04 1.04, 1.29 95 #> 115 NA, NA NA 1.35 1.12, 1.47 95 #> 116 NA, NA NA 1.66 1.48, 1.82 95 #> 117 NA, NA NA 1.67 1.47, 1.84 95 #> 118 NA, NA NA 1.50 1.2, 1.9 95 #> precision precision_ci_limits precision_ci truncation discretised censored #> 113 NA NA, NA NA NA FALSE TRUE #> 114 NA NA, NA NA NA FALSE TRUE #> 115 NA NA, NA NA NA FALSE TRUE #> 116 NA NA, NA NA NA FALSE TRUE #> 117 NA NA, NA NA NA FALSE TRUE #> 118 NA NA, NA NA NA FALSE TRUE #> right_truncated phase_bias_adjusted #> 113 FALSE FALSE #> 114 FALSE FALSE #> 115 FALSE FALSE #> 116 FALSE FALSE #> 117 FALSE FALSE #> 118 FALSE FALSE #> notes #> 113 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets #> 114 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets. This is a subset of data containing only mosquito-transmitted infections #> 115 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets. This is a subset of data containing only tramsission by transplant or transfusion. #> 116 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets #> 117 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets. This is a subset of data containing only mosquito-transmitted infections #> 118 Pooled analysis on several data sets, see Lessler et al. 2016 for references of datasets #> PMID DOI #> 113 24639305 10.4269/ajtmh.13-0403 #> 114 24639305 10.4269/ajtmh.13-0403 #> 115 24639305 10.4269/ajtmh.13-0403 #> 116 24639305 10.4269/ajtmh.13-0403 #> 117 24639305 10.4269/ajtmh.13-0403 #> 118 27821887 10.2471/BLT.16.174540"},{"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_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_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_params = c(shape = 2, scale = 1)) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is an — is_epiparam","title":"Check object is an — is_epiparam","text":"Check object ","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check object is an — is_epiparam","text":"","code":"is_epiparam(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check object is an — is_epiparam","text":"x R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check object is an — is_epiparam","text":"boolean logical, TRUE object FALSE .","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check object is an — is_epiparam","text":"","code":"eparam <- epiparam() is_epiparam(eparam) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if or object contain a distribution and\ndistribution parameters — is_parameterised","title":"Check if or object contain a distribution and\ndistribution parameters — is_parameterised","text":"Check object contain 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 object contain a distribution and\ndistribution parameters — is_parameterised","text":"","code":"is_parameterised(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if or object contain a distribution and\ndistribution parameters — is_parameterised","text":"x object. ... 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 object contain a distribution and\ndistribution parameters — is_parameterised","text":"single boolean logical vector boolean logicals length equal number rows . object row 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 object contain a distribution and\ndistribution 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 #> Unparameterised object is_parameterised(edist) #> [1] 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 an epiparam object — list_distributions","title":"List epidemiological distributions stored in an epiparam object — list_distributions","text":"function subsets epiparam object return chosen epidemiological distribution. results returned data frame better see returned distributions. default resulting data frame subset return disease, epidemiological distribution, probability distribution, author study year publication well sample size study. columns database required set subset_db = FALSE.","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 an epiparam object — list_distributions","text":"","code":"list_distributions( epiparam, epi_dist = c(\"incubation_period\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\", \"generation_time\", \"offspring_distribution\"), subset_db = TRUE )"},{"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 an epiparam object — list_distributions","text":"epiparam object. epi_dist character defining parameter listed: \"incubation\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\". \"incubation_period\" default epi_dist epi_dist specified incubation periods returned. subset_db boolean logical determines whether subset, defaults TRUE.","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 an epiparam object — list_distributions","text":"Adam Kucharski, Joshua W. Lambert","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 an epiparam object — list_distributions","text":"","code":"eparam <- epiparam() list_distributions(epiparam = eparam, epi_dist = \"incubation_period\") #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 incubation_period #> 4 COVID-19 incubation_period weibull #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period lnorm #> 7 COVID-19 incubation_period lnorm #> 8 COVID-19 incubation_period lnorm #> 9 COVID-19 incubation_period lnorm #> 10 COVID-19 incubation_period lnorm #> 11 COVID-19 incubation_period lnorm #> 12 COVID-19 incubation_period lnorm #> 13 COVID-19 incubation_period lnorm #> 14 COVID-19 incubation_period lnorm #> 15 COVID-19 incubation_period #> 16 COVID-19 incubation_period #> 17 Dengue incubation_period lnorm #> 18 Dengue incubation_period lnorm #> 19 Dengue incubation_period lnorm #> 20 Dengue incubation_period lnorm #> 21 Dengue incubation_period lnorm #> 22 Ebola Virus Disease incubation_period lnorm #> 23 Ebola Virus Disease incubation_period gamma #> 24 Ebola Virus Disease incubation_period gamma #> 25 Ebola Virus Disease incubation_period gamma #> 26 Ebola Virus Disease incubation_period gamma #> 27 Human Coronavirus incubation_period lnorm #> 28 Influenza incubation_period gamma #> 29 Influenza incubation_period lnorm #> 30 Influenza incubation_period lnorm #> 31 Influenza incubation_period lnorm #> 32 Influenza incubation_period lnorm #> 33 Influenza incubation_period gamma #> 34 Influenza incubation_period weibull #> 35 Influenza incubation_period lnorm #> 36 Influenza incubation_period lnorm #> 37 Influenza incubation_period lnorm #> 38 Influenza incubation_period weibull #> 39 Influenza incubation_period gamma #> 40 Influenza incubation_period weibull #> 41 Influenza incubation_period weibull #> 42 Influenza incubation_period weibull #> 43 Japanese Encephalitis incubation_period lnorm #> 44 Marburg Virus Disease incubation_period #> 45 Marburg Virus Disease incubation_period #> 46 Measles incubation_period lnorm #> 47 MERS incubation_period lnorm #> 48 MERS incubation_period gamma #> 49 Mpox incubation_period lnorm #> 50 Mpox incubation_period gamma #> 51 Mpox incubation_period lnorm #> 52 Mpox incubation_period lnorm #> 53 Mpox incubation_period lnorm #> 54 Mpox incubation_period #> 55 Mpox incubation_period #> 56 Mpox incubation_period #> 57 Mpox incubation_period #> 58 Mpox incubation_period #> 59 Mpox incubation_period #> 60 Parainfluenza incubation_period lnorm #> 61 Rhinovirus incubation_period lnorm #> 62 Rift Valley Fever incubation_period lnorm #> 63 RSV incubation_period lnorm #> 64 RSV incubation_period lnorm #> 65 RSV incubation_period lnorm #> 66 SARS incubation_period lnorm #> 67 West Nile Fever incubation_period lnorm #> 68 West Nile Fever incubation_period lnorm #> 69 West Nile Fever incubation_period lnorm #> 70 Yellow Fever incubation_period lnorm #> 71 Yellow Fever incubation_period lnorm #> 72 Zika Virus Disease incubation_period lnorm #> author year sample_size #> 1 Lessler_etal 2009 14 #> 2 Rudolph_etal 2014 21 #> 3 Alene_etal 2021 1453 #> 4 Bui_etal 2020 19 #> 5 Elias_etal 2021 28675 #> 6 Lauer_etal 2020 181 #> 7 Lauer_etal 2020 99 #> 8 Lauer_etal 2020 108 #> 9 Lauer_etal 2020 73 #> 10 Linton_etal 2020 52 #> 11 Linton_etal 2020 158 #> 12 Linton_etal 2020 52 #> 13 McAloon_etal 2020 1357 #> 14 McAloon_etal 2020 1269 #> 15 Men_etal 2020 59 #> 16 Rai_etal 2022 6241 #> 17 Chan_Johansson 2012 146 #> 18 Chan_Johansson 2012 146 #> 19 Chan_Johansson 2012 153 #> 20 Rudolph_etal 2014 169 #> 21 Rudolph_etal 2014 124 #> 22 Eichner_etal 2011 196 #> 23 WHO_Ebola_Response_Team 2015 49 #> 24 WHO_Ebola_Response_Team 2015 957 #> 25 WHO_Ebola_Response_Team 2015 792 #> 26 WHO_Ebola_ResponseTeam 2015 1798 #> 27 Lessler_etal 2009 13 #> 28 Ghani_etal 2009 16 #> 29 Lessler_etal 2009 151 #> 30 Lessler_etal 2009 90 #> 31 Lessler_etal 2009 78 #> 32 Lessler_etal 2009 124 #> 33 Nishiura_Inaba 2011 72 #> 34 Nishiura_Inaba 2011 72 #> 35 Reich_etal 2009 151 #> 36 Reich_etal 2009 151 #> 37 Tuite_etal 2010 316 #> 38 Virlogeux_etal 2015 229 #> 39 Virlogeux_etal 2015 229 #> 40 Virlogeux_etal 2016 395 #> 41 Virlogeux_etal 2016 173 #> 42 Virlogeux_etal 2016 222 #> 43 Rudolph_etal 2014 6 #> 44 Pavlin 2014 76 #> 45 Pavlin 2014 18 #> 46 Lessler_etal 2009 55 #> 47 Assiri_etal 2013 23 #> 48 Cowling_etal 2015 166 #> 49 Charniga_etal 2022 22 #> 50 Guzetta_etal 2022 255 #> 51 Madewell_etal 2022 35 #> 52 Madewell_etal 2022 36 #> 53 Miura_etal 2022 18 #> 54 Wang_etal 2022 16 #> 55 Wang_etal 2022 27 #> 56 Wang_etal 2022 114 #> 57 Wei_etal 2022 NA #> 58 Wei_etal 2022 NA #> 59 Wei_etal 2022 NA #> 60 Lessler_etal 2009 11 #> 61 Lessler_etal 2009 28 #> 62 Rudolph_etal 2014 23 #> 63 Lessler_etal 2009 24 #> 64 Reich_etal 2009 24 #> 65 Reich_etal 2009 24 #> 66 Lessler_etal 2009 157 #> 67 Rudolph_etal 2014 18 #> 68 Rudolph_etal 2014 8 #> 69 Rudolph_etal 2014 6 #> 70 Rudolph_etal 2014 91 #> 71 Rudolph_etal 2014 80 #> 72 Lessler_etal 2016 25 # the default for list_distributions() without any arguments is to return the # incubation period list_distributions(epiparam = eparam) #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 incubation_period #> 4 COVID-19 incubation_period weibull #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period lnorm #> 7 COVID-19 incubation_period lnorm #> 8 COVID-19 incubation_period lnorm #> 9 COVID-19 incubation_period lnorm #> 10 COVID-19 incubation_period lnorm #> 11 COVID-19 incubation_period lnorm #> 12 COVID-19 incubation_period lnorm #> 13 COVID-19 incubation_period lnorm #> 14 COVID-19 incubation_period lnorm #> 15 COVID-19 incubation_period #> 16 COVID-19 incubation_period #> 17 Dengue incubation_period lnorm #> 18 Dengue incubation_period lnorm #> 19 Dengue incubation_period lnorm #> 20 Dengue incubation_period lnorm #> 21 Dengue incubation_period lnorm #> 22 Ebola Virus Disease incubation_period lnorm #> 23 Ebola Virus Disease incubation_period gamma #> 24 Ebola Virus Disease incubation_period gamma #> 25 Ebola Virus Disease incubation_period gamma #> 26 Ebola Virus Disease incubation_period gamma #> 27 Human Coronavirus incubation_period lnorm #> 28 Influenza incubation_period gamma #> 29 Influenza incubation_period lnorm #> 30 Influenza incubation_period lnorm #> 31 Influenza incubation_period lnorm #> 32 Influenza incubation_period lnorm #> 33 Influenza incubation_period gamma #> 34 Influenza incubation_period weibull #> 35 Influenza incubation_period lnorm #> 36 Influenza incubation_period lnorm #> 37 Influenza incubation_period lnorm #> 38 Influenza incubation_period weibull #> 39 Influenza incubation_period gamma #> 40 Influenza incubation_period weibull #> 41 Influenza incubation_period weibull #> 42 Influenza incubation_period weibull #> 43 Japanese Encephalitis incubation_period lnorm #> 44 Marburg Virus Disease incubation_period #> 45 Marburg Virus Disease incubation_period #> 46 Measles incubation_period lnorm #> 47 MERS incubation_period lnorm #> 48 MERS incubation_period gamma #> 49 Mpox incubation_period lnorm #> 50 Mpox incubation_period gamma #> 51 Mpox incubation_period lnorm #> 52 Mpox incubation_period lnorm #> 53 Mpox incubation_period lnorm #> 54 Mpox incubation_period #> 55 Mpox incubation_period #> 56 Mpox incubation_period #> 57 Mpox incubation_period #> 58 Mpox incubation_period #> 59 Mpox incubation_period #> 60 Parainfluenza incubation_period lnorm #> 61 Rhinovirus incubation_period lnorm #> 62 Rift Valley Fever incubation_period lnorm #> 63 RSV incubation_period lnorm #> 64 RSV incubation_period lnorm #> 65 RSV incubation_period lnorm #> 66 SARS incubation_period lnorm #> 67 West Nile Fever incubation_period lnorm #> 68 West Nile Fever incubation_period lnorm #> 69 West Nile Fever incubation_period lnorm #> 70 Yellow Fever incubation_period lnorm #> 71 Yellow Fever incubation_period lnorm #> 72 Zika Virus Disease incubation_period lnorm #> author year sample_size #> 1 Lessler_etal 2009 14 #> 2 Rudolph_etal 2014 21 #> 3 Alene_etal 2021 1453 #> 4 Bui_etal 2020 19 #> 5 Elias_etal 2021 28675 #> 6 Lauer_etal 2020 181 #> 7 Lauer_etal 2020 99 #> 8 Lauer_etal 2020 108 #> 9 Lauer_etal 2020 73 #> 10 Linton_etal 2020 52 #> 11 Linton_etal 2020 158 #> 12 Linton_etal 2020 52 #> 13 McAloon_etal 2020 1357 #> 14 McAloon_etal 2020 1269 #> 15 Men_etal 2020 59 #> 16 Rai_etal 2022 6241 #> 17 Chan_Johansson 2012 146 #> 18 Chan_Johansson 2012 146 #> 19 Chan_Johansson 2012 153 #> 20 Rudolph_etal 2014 169 #> 21 Rudolph_etal 2014 124 #> 22 Eichner_etal 2011 196 #> 23 WHO_Ebola_Response_Team 2015 49 #> 24 WHO_Ebola_Response_Team 2015 957 #> 25 WHO_Ebola_Response_Team 2015 792 #> 26 WHO_Ebola_ResponseTeam 2015 1798 #> 27 Lessler_etal 2009 13 #> 28 Ghani_etal 2009 16 #> 29 Lessler_etal 2009 151 #> 30 Lessler_etal 2009 90 #> 31 Lessler_etal 2009 78 #> 32 Lessler_etal 2009 124 #> 33 Nishiura_Inaba 2011 72 #> 34 Nishiura_Inaba 2011 72 #> 35 Reich_etal 2009 151 #> 36 Reich_etal 2009 151 #> 37 Tuite_etal 2010 316 #> 38 Virlogeux_etal 2015 229 #> 39 Virlogeux_etal 2015 229 #> 40 Virlogeux_etal 2016 395 #> 41 Virlogeux_etal 2016 173 #> 42 Virlogeux_etal 2016 222 #> 43 Rudolph_etal 2014 6 #> 44 Pavlin 2014 76 #> 45 Pavlin 2014 18 #> 46 Lessler_etal 2009 55 #> 47 Assiri_etal 2013 23 #> 48 Cowling_etal 2015 166 #> 49 Charniga_etal 2022 22 #> 50 Guzetta_etal 2022 255 #> 51 Madewell_etal 2022 35 #> 52 Madewell_etal 2022 36 #> 53 Miura_etal 2022 18 #> 54 Wang_etal 2022 16 #> 55 Wang_etal 2022 27 #> 56 Wang_etal 2022 114 #> 57 Wei_etal 2022 NA #> 58 Wei_etal 2022 NA #> 59 Wei_etal 2022 NA #> 60 Lessler_etal 2009 11 #> 61 Lessler_etal 2009 28 #> 62 Rudolph_etal 2014 23 #> 63 Lessler_etal 2009 24 #> 64 Reich_etal 2009 24 #> 65 Reich_etal 2009 24 #> 66 Lessler_etal 2009 157 #> 67 Rudolph_etal 2014 18 #> 68 Rudolph_etal 2014 8 #> 69 Rudolph_etal 2014 6 #> 70 Rudolph_etal 2014 91 #> 71 Rudolph_etal 2014 80 #> 72 Lessler_etal 2016 25 # this same process can be achieved when loading the library eparam <- epiparam(epi_dist = \"incubation_period\") # filtering for onset to death list_distributions(epiparam = eparam, epi_dist = \"onset_to_death\") #> [1] disease epi_distribution prob_distribution author #> [5] year sample_size #> <0 rows> (or 0-length row.names)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an object from a list of input from an\n object — make_epidist","title":"Create an object from a list of input from an\n object — make_epidist","text":"Unpacks list inputs object helper, including parameters uncertainty correct type probability distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an object from a list of input from an\n object — make_epidist","text":"","code":"make_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an object from a list of input from an\n object — make_epidist","text":"x List data used construct object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an object from a list of input from an\n object — make_epidist","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Set names for class — names<-.epiparam","title":"Set names for class — names<-.epiparam","text":"modifying names invalidates object (defined invariants, encoded validate_epiparam()) subsetting return data frame message console stating class object converted data frame attributes class preserved.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set names for class — names<-.epiparam","text":"","code":"# S3 method for epiparam names(x) <- value"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set names for class — names<-.epiparam","text":"x R object. value character vector length x, NULL.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set names for class — names<-.epiparam","text":"epiparam object data.frame","code":""},{"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 wiht 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_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for class — new_epiparam","title":"Constructor for class — new_epiparam","text":"constructor reads data stored internally package subsets epidemiological distribution (epi_dist).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for class — new_epiparam","text":"","code":"new_epiparam(epi_dist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for class — new_epiparam","text":"epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for class — new_epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Constructor for class — new_epiparam","text":"","code":"eparam <- epiparameter:::new_epiparam(\"all\")"},{"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.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for class — print.epiparam","title":"Print method for class — print.epiparam","text":"Print method class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for class — print.epiparam","text":"","code":"# S3 method for epiparam print(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for class — print.epiparam","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for class — print.epiparam","text":"Invisibly returns . Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for class — print.epiparam","text":"","code":"epiparam <- epiparam() epiparam #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown>"},{"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( disease = \"ebola\", epi_dist = \"incubation_period\", prob_distribution = \"gamma\", prob_distribution_params = c(shape = 1, scale = 1) ), extrinsic = 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/sub-.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset method for class — [.epiparam","title":"Subset method for class — [.epiparam","text":"subsetting invalidates object (defined invariants, encoded validate_epiparam()) subsetting return data frame message console stating class object converted data.frame attributes class preserved.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/sub-.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset method for class — [.epiparam","text":"","code":"# S3 method for epiparam [(epiparam, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/sub-.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset method for class — [.epiparam","text":"epiparam object. ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/sub-.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset method for class — [.epiparam","text":"epiparam object data.frame","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Summary method for class — summary.epiparam","title":"Summary method for class — summary.epiparam","text":"Summary method class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summary method for class — summary.epiparam","text":"","code":"# S3 method for epiparam summary(object, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summary method for class — summary.epiparam","text":"object object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summary method for class — summary.epiparam","text":"data frame information","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Summary method for class — summary.epiparam","text":"","code":"x <- epiparam() summary(x) #> $num_entries #> [1] 118 #> #> $num_diseases #> [1] 23 #> #> $num_delay_dist #> [1] 95 #> #> $num_offspring_dist #> [1] 10 #> #> $num_studies #> [1] 57 #> #> $num_continuous_distributions #> [1] 118 #> #> $num_discrete_distributions #> [1] 0 #> #> $num_vector_borne_diseases #> [1] 2 #>"},{"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_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for class — validate_epiparam","title":"Validator for class — validate_epiparam","text":"Validator class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validator for class — validate_epiparam","text":"","code":"validate_epiparam(epiparam, reconstruct = FALSE)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validator for class — validate_epiparam","text":"epiparam object. reconstruct boolean logical determining whether validation class specific. TRUE input object must type (default), FALSE input object can another class, e.g. data frame. argument used reconstruction operations see epiparam_reconstruct().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validator for class — validate_epiparam","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/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 distribution 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. Contributions can added google sheet. 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 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":"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":""},{"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. Across site performed search. 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. database unsuitable papers kept remind maintainers papers included aids updating databse (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 distirbution), 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. minimal dataset required included epiparameter library : Name disease Type distribution Author(s) paper year publication transmission mode pathogen (.e. directly transmitted vector-borne) Whether distribution extrinsic (e.g. extrinsic incubation period). disease vector-borne NA. type distribution fitted, either distribution fit best-fit set candidate distributions Parameter distribution (e.g. shape scale case gamma, meanlog sdlog case lognormal, etc.) Mean standard deviation (equivalently variance coefficient variation) Median range two quantiles. Ideally lower quantile (q < 0.5) upper quantile (q > 0.5) ensure reliable estimation parameters Whether distribution fitted discretised, boolean (true false). Digital Object Identifier (DOI) paper Data recommended essential: Name pathogen Sample size data used fit distribution region data collected, either natioanl, continental global level Type vector Uncertainty estimated parameters summary statistics, needs provided type inference used (e.g. maximum likelihood bayesian) avoid potential misuse uncertainty (e.g. mistaking confindence interval credible interval) Additional unique identifiers paper, exampel PubMed ID (PMID) Whether distribution fitted adjusted phase bias Whether disribution used interval-censoring Whether distribution right-truncated truncation point ‘Notes’: can include general statements distribution methodology used paper. notes can accessed using package make users aware possible limitations distribution parameters may fit categories 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 methological 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 skrinking 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 subsquent 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/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 three new classes working epidemiological parameters R: : library epidemiolgical parameters : singular set epidemiolgical parameters : singular set epidemiolgical parameters vector-borne disease containing extrinsic intrinsic distribution. object contains two sets parameters, one human (intrinsic) 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. Extra arguments also available epidist() add information uncertainty citation information.","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}. class introduced enable users easily explore range parameters available. library can read R using epiparam() function. default entries library supplied. class custom printing method gives summary information included database including number distributions, number diseases, number different studies among summary metrics, well first six rows diseases, epidemiological distributions (epi_distribution) probability distribution (prob_distribution). class based (.e. inherits ) data frame, therefore subsetting manipulation can carried , including head() tail() database. epidemiological library contains multiple columns, storing different features parameter: subsetting object removes one essential columns object converted data frame. example, removing disease column causes object converted data frame. See Epiverse-TRACE blog post extending data frames technical description. see full list diseases distributions stored library use list_distributions() function. show first six rows output. details data collation library parameters can found Data Collation Synthesis Protocol vignette.","code":"epi_dist_db <- epiparam() epi_dist_db #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown> head(epi_dist_db)[, 1:4] #> disease pathogen epi_distribution author #> 1 Adenovirus Adenovirus incubation_period Lessler_etal #> 2 Chikungunya Chikungunya Virus incubation_period Rudolph_etal #> 3 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 4 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 5 COVID-19 SARS-CoV-2 incubation_period Alene_etal #> 6 COVID-19 SARS-CoV-2 incubation_period Bui_etal tail(epi_dist_db)[, 1:4] #> disease pathogen epi_distribution author #> 113 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 114 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 115 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 116 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 117 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 118 Zika Virus Disease Zika Virus incubation_period Lessler_etal colnames(epi_dist_db) #> [1] \"disease\" \"pathogen\" \"epi_distribution\" #> [4] \"author\" \"title\" \"journal\" #> [7] \"year\" \"sample_size\" \"region\" #> [10] \"transmission_mode\" \"vector\" \"extrinsic\" #> [13] \"prob_distribution\" \"inference_method\" \"mean\" #> [16] \"mean_ci_limits\" \"mean_ci\" \"sd\" #> [19] \"sd_ci_limits\" \"sd_ci\" \"quantile_2.5\" #> [22] \"quantile_5\" \"quantile_25\" \"median\" #> [25] \"median_ci_limits\" \"median_ci\" \"quantile_75\" #> [28] \"quantile_87.5\" \"quantile_95\" \"quantile_97.5\" #> [31] \"lower_range\" \"upper_range\" \"shape\" #> [34] \"shape_ci_limits\" \"shape_ci\" \"scale\" #> [37] \"scale_ci_limits\" \"scale_ci\" \"meanlog\" #> [40] \"meanlog_ci_limits\" \"meanlog_ci\" \"sdlog\" #> [43] \"sdlog_ci_limits\" \"sdlog_ci\" \"dispersion\" #> [46] \"dispersion_ci_limits\" \"dispersion_ci\" \"precision\" #> [49] \"precision_ci_limits\" \"precision_ci\" \"truncation\" #> [52] \"discretised\" \"censored\" \"right_truncated\" #> [55] \"phase_bias_adjusted\" \"notes\" \"PMID\" #> [58] \"DOI\" epi_dist_df <- epi_dist_db[colnames(epi_dist_db) != \"disease\"] #> Removing crucial column in `` returning `` head(list_distributions(epi_dist_db)) #> disease epi_distribution prob_distribution author year sample_size #> 1 Adenovirus incubation_period lnorm Lessler_etal 2009 14 #> 2 Chikungunya incubation_period lnorm Rudolph_etal 2014 21 #> 3 COVID-19 incubation_period Alene_etal 2021 1453 #> 4 COVID-19 incubation_period weibull Bui_etal 2020 19 #> 5 COVID-19 incubation_period Elias_etal 2021 28675 #> 6 COVID-19 incubation_period lnorm Lauer_etal 2020 181"},{"path":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"single-set-of-epidemiolgical-parameters","dir":"Articles","previous_headings":"Working with {epiparameter} data","what":"Single set of epidemiolgical parameters","title":"Getting Started with {epiparameter}","text":"second class introduced {epiparameter} package class. holds single set epidemiological parameters. object can converted one rows object can created manually. First show conversion → . uses as_epidist() function. object also custom printing method shows disease, pathogen (known), epidemiological distribution, citation study parameters probability distribution parameter distribution (available). opposite conversion can also achieved using as_epiparam(). two alternatives reading objects subsetting . Extract directly library epidist_db(). Create manually constructor function. epidist_db() allows direct subsetting library returns single set epidemiological parameters. Additionally using entries {epiparameter} library, objects can manually created. may especially useful new parameter estimates become available yet incorporated library.","code":"# find entry for COVID-19 epi_dist_covid <- epi_dist_db[epi_dist_db$disease == \"COVID-19\", ] # find entry for COVID-19 incubation period epi_dist_covid_incub <- epi_dist_covid[epi_dist_covid$epi_distribution == \"incubation_period\", ] # nolint # select one of the COVID-19 incubation period covid_incub <- epi_dist_covid_incub[10, ] # convert epiparam entry to epidist covid_incub <- as_epidist(covid_incub) #> Using Linton, etal (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 #> . #> To retrieve the citation use the 'get_citation' function covid_incub #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton, etal (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 as_epiparam(covid_incub) #> Epiparam object #> Number of distributions in library: 1 #> Number of diseases: 1 #> Number of delay distributions: 1 #> Number of offspring distributions: 0 #> Number of studies in library: 1 #> #> disease epi_distribution prob_distribution #> 1 COVID-19 incubation_period lnorm #> <0 more rows & 55 more cols not shown> epidist_db( disease = \"COVID-19\", epi_dist = \"incubation_period\", author = \"Bui_etal\" ) #> Using Bui, etal (2020). \"Estimation of the incubation period of COVID-19 in #> Vietnam.\" _PLoS One_. doi:10.1371/journal.pone.0243889 #> . #> To retrieve the citation use the 'get_citation' function #> Numerical approximation used, results may be unreliable. #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Bui, etal (2020). \"Estimation of the incubation period of COVID-19 in #> Vietnam.\" _PLoS One_. doi:10.1371/journal.pone.0243889 #> . #> Distribution: weibull #> Parameters: #> shape: 2.217 #> scale: 7.226 ebola_incubation <- 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"},{"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":"adding-library-entries","dir":"Articles","previous_headings":"","what":"Adding library entries","title":"Getting Started with {epiparameter}","text":"set epidemiological parameter inferred known user yet incorporated {epiparameter} database, parameters can manually added library. add entries library provide function bind data objects: bind_epiparam(). function provided multiple data types (classes) can bound existing object (subclass ). bind_epiparam() can bind , (including ), lists. Note adds parameters library ( object) environment, save database file package. binding columns use either tibble::add_column() dplyr::bind_cols(). Using cbind() unclass object (.e. convert ). Note dplyr::bind_cols() print message returned, case.","code":"bind_epiparam(epiparam = epi_dist_db, epi_obj = ebola_incubation) #> Epiparam object #> Number of distributions in library: 119 #> Number of diseases: 24 #> Number of delay distributions: 96 #> Number of offspring distributions: 10 #> Number of studies in library: 58 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <113 more rows & 55 more cols not shown> bind_epiparam(epiparam = epi_dist_db, epi_obj = as_epiparam(ebola_incubation)) #> Epiparam object #> Number of distributions in library: 119 #> Number of diseases: 24 #> Number of delay distributions: 96 #> Number of offspring distributions: 10 #> Number of studies in library: 58 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <113 more rows & 55 more cols not shown>"},{"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":"density(ebola_incubation, at = 0.5) #> [1] 0.1902978 cdf(ebola_incubation, q = 0.5) #> [1] 0.04521373 quantile(ebola_incubation, p = 0.5) #> [1] 2.718282 generate(ebola_incubation, times = 10) #> [1] 14.4432826 2.0297665 10.6703451 9.1135557 0.4496396 10.5164219 #> [7] 11.8342655 2.4529662 0.5389239 2.1628564"},{"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":"https://epiverse-trace.github.io/epiparameter/articles/epiparameter.html","id":"contributing-to-epiparameter","dir":"Articles","previous_headings":"","what":"Contributing to {epiparameter}","title":"Getting Started with {epiparameter}","text":"library epidemiological parameters living database, new studies published hope incorporate . Due large time requirement searching recording parameters database welcome others add parameters contributing spreadsheet. incorporated database package maintainers. See Data Collation Synthesis Protocol vignette information contributing library epidemiological parameters.","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. # 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 #> 3.358187 1.284186 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 2.646129 # 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: library class, underneath data frame. entry library can converted object used. object can plotted.","code":"library(epiparameter) eparams <- epiparam() eparams #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown> influenza_incubation <- as_epidist(eparams[12, ]) #> Using Linton, etal (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 #> . #> To retrieve the citation use the 'get_citation' function influenza_incubation #> Disease: COVID-19 #> Pathogen: SARS-CoV-2 #> Epi Distribution: incubation period #> Study: Linton, etal (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 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_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert to — as_epidist","title":"Convert to — as_epidist","text":"Convert entries (rows) object one list several objects. Epidemiological distributions parameters can converted database entries (.e. rows ) objects order use distribution functions (see ?epidist_distribution_functions) methods class.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert to — as_epidist","text":"","code":"as_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert to — as_epidist","text":"x object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert to — as_epidist","text":" object list objects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epidist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert to — as_epidist","text":"","code":"# \\donttest{ eparam <- epiparam() as_epidist(eparam[1, ]) #> Using Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> . #> To retrieve the citation use the 'get_citation' function #> Stochastic numerical optimisation used. #> Rerun function multiple times to check global optimum is found #> Disease: Adenovirus #> Pathogen: Adenovirus #> Epi Distribution: incubation period #> Study: Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> . #> Distribution: lnorm #> Parameters: #> meanlog: 1.720 #> sdlog: 0.225 # }"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert an object to an object — as_epiparam","title":"Convert an object to an object — as_epiparam","text":"Convert object object","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert an object to an object — as_epiparam","text":"","code":"as_epiparam(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert an object to an object — as_epiparam","text":"x object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert an object to an object — as_epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/as_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert an object to an object — as_epiparam","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 as_epiparam(edist) #> Epiparam object #> Number of distributions in library: 1 #> Number of diseases: 1 #> Number of delay distributions: 1 #> Number of offspring distributions: 0 #> Number of studies in library: 1 #> #> disease epi_distribution prob_distribution #> 1 ebola incubation_period lnorm #> <0 more rows & 55 more cols not shown>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Bind an epi object to an object — bind_epiparam","title":"Bind an epi object to an object — bind_epiparam","text":"Bind epi data class epiparameter (, , ) data frame object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bind an epi object to an object — bind_epiparam","text":"","code":"bind_epiparam(epiparam, epi_obj)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bind an epi object to an object — bind_epiparam","text":"epiparam object. epi_obj Either , , list objects. can also data frame long columns conform columns object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bind an epi object to an object — bind_epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bind an epi object to an object — bind_epiparam","text":" class holds library epidemiological parameters stored epiparameter R package can manipulated. bind_epiparam() function allows users add entries library binding bottom existing object loaded R. returned bind_epiparam() contains matching columns input objects. Therefore, one input objects contains extra columns present input object missing returned object. also applies whether binding objects. binding objects missing data fields given default value binding.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/bind_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bind an epi object to an object — bind_epiparam","text":"","code":"eparam <- epiparam() 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 bind_epiparam(eparam, edist) #> Epiparam object #> Number of distributions in library: 119 #> Number of diseases: 24 #> Number of delay distributions: 96 #> Number of offspring distributions: 10 #> Number of studies in library: 58 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <113 more rows & 55 more cols not shown>"},{"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, summary_stats, sample_size = NA)"},{"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). 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(q_2.5 = 0.2, q_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/cash-set-.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Set accessor for epiparam class — $<-.epiparam","title":"Set accessor for epiparam class — $<-.epiparam","text":"Set accessor epiparam class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/cash-set-.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set accessor for epiparam class — $<-.epiparam","text":"","code":"# S3 method for epiparam $(x, name) <- value"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/cash-set-.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set accessor for epiparam class — $<-.epiparam","text":"x epiparam object name literal character string name (possibly backtick quoted). extraction, normally (see ‘Environments’) partially matched names object. value typically array-like R object similar class x.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/cash-set-.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set accessor for epiparam class — $<-.epiparam","text":"epiparam object data.frame","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/check_optim_conv.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the optimisation of distribution parameters has converged to\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_epidist_name.html","id":null,"dir":"Reference","previous_headings":"","what":"Standardise the names of epidemiological distributions — clean_epidist_name","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"Standardise names epidemiological distributions","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"","code":"clean_epidist_name(epi_dist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"epi_dist character string name distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"character vector equal length input.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/clean_epidist_name.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Standardise the names of epidemiological distributions — clean_epidist_name","text":"","code":"clean_epidist_name(\"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.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 = NA_character_, 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 character string surname first author. can underscore separated second author, underscore separated \"etal\" two authors. 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 = \"Smith_etal\", year = 2002, title = \"COVID-19 incubation period\", journal = \"Epi Journal\", DOI = \"10.19832/j.1366-9516.2012.09147.x\" ) #> Using Smith, etal (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, etal (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_, dispersion = NA_real_, dispersion_ci_limits = c(NA_real_, NA_real_), dispersion_ci = NA_real_, lower_range = NA_real_, upper_range = NA_real_, quantiles = c(q_2.5 = NA_real_, q_5 = NA_real_, q_25 = NA_real_, q_50 = NA_real_, q_75 = NA_real_, q_95 = NA_real_, q_97.5 = 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. dispersion numeric dispersion parameter distribution. dispersion_ci_limits numeric vector length two confidence interval around dispersion. dispersion_ci numeric specifying confidence interval width dispersion parameter. 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) #> $centre_spread #> $centre_spread$mean #> [1] 5 #> #> $centre_spread$mean_ci_limits #> [1] NA NA #> #> $centre_spread$mean_ci #> [1] NA #> #> $centre_spread$sd #> [1] 2 #> #> $centre_spread$sd_ci_limits #> [1] NA NA #> #> $centre_spread$sd_ci #> [1] NA #> #> $centre_spread$median #> [1] NA #> #> $centre_spread$median_ci_limits #> [1] NA NA #> #> $centre_spread$median_ci #> [1] NA #> #> #> $quantiles #> q_2.5 q_5 q_25 q_50 q_75 q_95 q_97.5 #> NA NA NA NA NA NA NA #> #> $range #> $range$lower_range #> [1] NA #> #> $range$upper_range #> [1] NA #> #> #> $dispersion #> $dispersion$dispersion #> [1] NA #> #> $dispersion$dispersion_ci_limits #> [1] NA NA #> #> $dispersion$dispersion_ci #> [1] 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 ) #> $centre_spread #> $centre_spread$mean #> [1] 4 #> #> $centre_spread$mean_ci_limits #> [1] 2.1 5.7 #> #> $centre_spread$mean_ci #> [1] 95 #> #> $centre_spread$sd #> [1] 0.7 #> #> $centre_spread$sd_ci_limits #> [1] 0.3 1.1 #> #> $centre_spread$sd_ci #> [1] 95 #> #> $centre_spread$median #> [1] NA #> #> $centre_spread$median_ci_limits #> [1] NA NA #> #> $centre_spread$median_ci #> [1] NA #> #> #> $quantiles #> q_2.5 q_5 q_25 q_50 q_75 q_95 q_97.5 #> NA NA NA NA NA NA NA #> #> $range #> $range$lower_range #> [1] NA #> #> $range$upper_range #> [1] NA #> #> #> $dispersion #> $dispersion$dispersion #> [1] NA #> #> $dispersion$dispersion_ci_limits #> [1] NA NA #> #> $dispersion$dispersion_ci #> [1] NA #> #> # median and range create_epidist_summary_stats( median = 5, lower_range = 1, upper_range = 13 ) #> $centre_spread #> $centre_spread$mean #> [1] NA #> #> $centre_spread$mean_ci_limits #> [1] NA NA #> #> $centre_spread$mean_ci #> [1] NA #> #> $centre_spread$sd #> [1] NA #> #> $centre_spread$sd_ci_limits #> [1] NA NA #> #> $centre_spread$sd_ci #> [1] NA #> #> $centre_spread$median #> [1] 5 #> #> $centre_spread$median_ci_limits #> [1] NA NA #> #> $centre_spread$median_ci #> [1] NA #> #> #> $quantiles #> q_2.5 q_5 q_25 q_50 q_75 q_95 q_97.5 #> NA NA NA NA NA NA NA #> #> $range #> $range$lower_range #> [1] 1 #> #> $range$upper_range #> [1] 13 #> #> #> $dispersion #> $dispersion$dispersion #> [1] NA #> #> $dispersion$dispersion_ci_limits #> [1] NA NA #> #> $dispersion$dispersion_ci #> [1] NA #> #>"},{"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/df_reconstruct.html","id":null,"dir":"Reference","previous_headings":"","what":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":"Transplant attributes one input () input (x)","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/df_reconstruct.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":"","code":"df_reconstruct(x, to)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/df_reconstruct.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":"x data.frame subclass data.frame (e.g. ). reference object, case object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/df_reconstruct.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transplant the attributes of one input (to) to the other input (x) — df_reconstruct","text":" object.","code":""},{"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, ...) # 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 epiparam() as_epidist(). 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 wiht 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 'mealog' '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 = \"Smith_etal\", 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, etal (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 an object(s) directly from the epiparameter library\n(database) — epidist_db","title":"Create an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"Extract object(s) directly library epidemiological parameters. bypasses need read object convert object. 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 an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"","code":"epidist_db( disease, epi_dist = c(\"incubation_period\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\", \"generation_time\", \"offspring_distribution\"), 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 an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"disease character string specifying disease. epi_dist character string specifying epidemiological distribution. author character string specifying author study reporting distribution. subset Either NULL valid R expressions evaluates logicals subset rows , function can applied directly object. argument allows general subsetting can combined subsetting done disease epidist arguments (author specified). left NULL (default) subsetting carried . expression specified without using data object name (e.g. df$var) instead just var supplied. words, argument works subset argument subset(). similar using 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 an 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 an 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 &.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epidist_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an object(s) directly from the epiparameter library\n(database) — epidist_db","text":"","code":"epidist_db(disease = \"influenza\", epi_dist = \"serial_interval\") #> Using Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> To retrieve the citation use the 'get_citation' function #> Disease: Influenza #> Pathogen: Influenza-A-H1N1Pdm #> Epi Distribution: serial interval #> Study: Ghani, etal (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 # comparison between using `epidist_db()` and `epiparam()` with # `as_epidist()` # load influenza serial interval from database edist <- epidist_db(disease = \"influenza\", epi_dist = \"serial_interval\") #> Using Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> To retrieve the citation use the 'get_citation' function # load database of serial intervals eparam <- epiparam(epi_dist = \"serial_interval\") # subset database to only influenza entries eparam <- eparam[clean_disease(eparam$disease) == \"influenza\", ] # convert to `epidist` edist2 <- as_epidist(eparam) #> Using Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> To retrieve the citation use the 'get_citation' function # check the two methods produce the same `epidist` object identical(edist, edist2) #> [1] TRUE # example using custom subsetting eparam <- epidist_db( disease = \"SARS\", epi_dist = \"offspring_distribution\", subset = sample_size > 40 ) #> Using Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> To retrieve the citation use the 'get_citation' function # example using functional subsetting eparam <- epidist_db( disease = \"COVID-19\", epi_dist = \"incubation_period\", subset = is_parameterised ) #> Returning 2 results that match the criteria (2 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 list(author = list(list(given = NULL, family = \"Lloyd-Smith\", role = NULL, email = NULL, comment = NULL), list(given = NULL, family = \"etal\", role = NULL, email = NULL, comment = NULL)), year = \"2005\", title = \"Superspreading and the effect of individual variation on disease emergence\", journal = \"Nature\", doi = \"10.1038/nature04153\", pmid = \"16292310\"). #> 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, ...) # 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 . 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] 2.7914140 1.1741894 1.3286020 0.2825627 0.4140444 0.5128917 0.1931127 #> [8] 0.0831748 0.5239166 0.1059182 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] 1.1349881 2.8008354 2.4924802 0.2825947 3.8515281 1.5624448 0.5885463 #> [8] 0.6735860 1.8987479 0.1601222 #> #> $extrinsic #> [1] 1.043827886 0.881601493 0.157763926 0.050841083 1.336452325 0.007527032 #> [7] 0.490471171 3.405340406 0.871274401 0.400682147 #>"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an object — epiparam","title":"Create an object — epiparam","text":" class holds information epidemiological distribution estimated parameters well information metadata. library epidemiological parameters compiled primary literature sources. object can used compare availability distribution certain disease pathogen, refine , example, region sample size. Additionally, class can subset converted objects used epidemiological analysis delay distribution offspring distribution required. epiparam() function reads library epidemiological parameters {epiparameter} memory stores object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an object — epiparam","text":"","code":"epiparam( epi_dist = c(\"all\", \"incubation_period\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\", \"generation_time\", \"offspring_distribution\") )"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an object — epiparam","text":"epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an object — epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an object — epiparam","text":" object certain protected fields, thus one protected fields removed subsetting columns error returned. subsetting checks carried validate_epiparam(). Data can added objects using bind_epiparam(), can add information , , , lists objects, data frames correct columns existing object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an object — epiparam","text":"","code":"# the object can be made without arguments eparam <- epiparam() # specifying incubation periods incub_eparam <- epiparam(\"incubation\") # subset by disease influenza_dists <- eparam[eparam$disease == \"influenza\", ]"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":null,"dir":"Reference","previous_headings":"","what":"Check whether the object is valid — epiparam_can_reconstruct","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"wrapper validate_epiparam() tryCatch() order error input object invalid returns TRUE FALSE object valid. object valid can \"reconstructed\" downgraded data.frame.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"","code":"epiparam_can_reconstruct(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"x data.frame subclass data.frame (e.g. ).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_can_reconstruct.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check whether the object is valid — epiparam_can_reconstruct","text":"boolean logical.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":null,"dir":"Reference","previous_headings":"","what":"Decide whether object can be reconstructed from input — epiparam_reconstruct","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":"Uses epiparam_can_reconstruct() determine whether data input can reconstructed valid object. can , returned data frame.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":"","code":"epiparam_reconstruct(x, to)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":"x data.frame subclass data.frame (e.g. ). reference object, case object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/epiparam_reconstruct.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Decide whether object can be reconstructed from input — epiparam_reconstruct","text":" object (input valid) data.frame.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/extract_param.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the parameters of a parametric probability distribution from\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 #> 5.339552 1.995358"},{"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.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Format method for class — format.epiparam","title":"Format method for class — format.epiparam","text":"Format method class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format method for class — format.epiparam","text":"","code":"# S3 method for epiparam format(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format method for class — format.epiparam","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format method for class — format.epiparam","text":"Invisibly returns . Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/format.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format method for class — format.epiparam","text":"","code":"x <- epiparam() format(x) #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown>"},{"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( disease = \"ebola\", epi_dist = \"incubation_period\", prob_distribution = \"gamma\", prob_distribution_params = c(shape = 1, scale = 1) ), extrinsic = 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 objects — get_citation","title":"Extract citation information from or objects — get_citation","text":"Extract citation information 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 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 objects — get_citation","text":"x object. ... Extra arguments passed method.","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 objects — get_citation","text":"single character string list character string citations. Length list output equal number rows 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 objects — get_citation","text":"","code":"# example with epidist eparam <- epiparam() edist <- as_epidist(eparam[12, ]) #> Using Linton, etal (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 #> . #> To retrieve the citation use the 'get_citation' function get_citation(edist) #> Linton, etal (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 #> . # example with epiparam eparam <- epiparam() get_citation(eparam) #> [[1]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-6 #> . #> #> [[2]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[3]] #> Linton, etal (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 #> . #> #> [[4]] #> Linton, etal (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 #> . #> #> [[5]] #> Alene, etal (2021). “Serial interval and incubation period of COVID-19: #> a systematic review and meta-analysis.” _BMC Infectious Diseases_. #> doi:10.1186/s12879-021-05950-x #> . #> #> [[6]] #> Bui, etal (2020). “Estimation of the incubation period of COVID-19 in #> Vietnam.” _PLoS One_. doi:10.1371/journal.pone.0243889 #> . #> #> [[7]] #> Elias, etal (2021). “The incubation period of COVID-19: A #> meta-analysis.” _International Journal of Infectious Diseases_. #> doi:10.1016/j.ijid.2021.01.069 #> . #> #> [[8]] #> Lauer, etal (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 #> . #> #> [[9]] #> Lauer, etal (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 #> . #> #> [[10]] #> Lauer, etal (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 #> . #> #> [[11]] #> Lauer, etal (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 #> . #> #> [[12]] #> Linton, etal (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 #> . #> #> [[13]] #> Linton, etal (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 #> . #> #> [[14]] #> Linton, etal (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 #> . #> #> [[15]] #> McAloon, etal (2020). “Incubation period of COVID-19: a rapid #> systematic review and meta-analysis of observational research.” _BMJ #> Open_. doi:10.1136/bmjopen-2020-039652 #> . #> #> [[16]] #> McAloon, etal (2020). “Incubation period of COVID-19: a rapid #> systematic review and meta-analysis of observational research.” _BMJ #> Open_. doi:10.1136/bmjopen-2020-039652 #> . #> #> [[17]] #> Men, etal (2020). “Estimate the incubation period of coronavirus 2019 #> (COVID-19).” _medRxiv_. doi:10.1101/2020.02.24.20027474 #> . #> #> [[18]] #> Rai, etal (2022). “Incubation period for COVID-19: a systematic review #> and meta-analysis.” _Zeitschrift fur Gesundheitswissenschaften_. #> doi:10.1007/s10389-021-01478-1 #> . #> #> [[19]] #> Linton, etal (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 #> . #> #> [[20]] #> Linton, etal (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 #> . #> #> [[21]] #> Linton, etal (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 #> . #> #> [[22]] #> Linton, etal (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 #> . #> #> [[23]] #> Linton, etal (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 #> . #> #> [[24]] #> Linton, etal (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 #> . #> #> [[25]] #> Alene, etal (2021). “Serial interval and incubation period of COVID-19: #> a systematic review and meta-analysis.” _BMC Infectious Diseases_. #> doi:10.1186/s12879-021-05950-x #> . #> #> [[26]] #> Chan, Johansson (2012). “The Incubation Periods of Dengue Viruses.” #> _PLoS One_. doi:10.1371/journal.pone.0050972 #> . #> #> [[27]] #> Chan, Johansson (2012). “The Incubation Periods of Dengue Viruses.” #> _PLoS One_. doi:10.1371/journal.pone.0050972 #> . #> #> [[28]] #> Chan, Johansson (2012). “The Incubation Periods of Dengue Viruses.” #> _PLoS One_. doi:10.1371/journal.pone.0050972 #> . #> #> [[29]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[30]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[31]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[32]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[33]] #> Eichner, etal (2011). “Incubation period of ebola hemorrhagic virus #> subtype zaire.” _Osong Public Health and Research Perspectives_. #> doi:10.1016/j.phrp.2011.04.001 #> . #> #> [[34]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414993 #> . #> #> [[35]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414994 #> . #> #> [[36]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414995 #> . #> #> [[37]] #> WHO, Ebola, ResponseTeam (2015). “West African Ebola Epidemic after One #> Year — Slowing but Not Yet under Control.” _The New England Journal of #> Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[38]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[39]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[40]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[41]] #> Barry, etal (2018). “Outbreak of Ebola virus disease in the Democratic #> Republic of the Congo, April–May, 2018: an epidemiological study.” _The #> Lancet_. doi:10.1016/S0140-6736(18)31387-4 #> . #> #> [[42]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[43]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[44]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[45]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[46]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[47]] #> WHO, Ebola, Response, Team (2015). “West African Ebola Epidemic after #> One Year — Slowing but Not Yet under Control.” _The New England Journal #> of Medicine_. doi:10.1056/NEJMc1414992 #> . #> #> [[48]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[49]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-7 #> . #> #> [[50]] #> Lessler, etal (2009). “Outbreak of 2009 Pandemic Influenza A (H1N1) at #> a New York City School.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa0906089 . #> #> [[51]] #> Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> #> [[52]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-9 #> . #> #> [[53]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-10 #> . #> #> [[54]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-11 #> . #> #> [[55]] #> Lessler, etal (2009). “Outbreak of 2009 Pandemic Influenza A (H1N1) at #> a New York City School.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa0906089 . #> #> [[56]] #> Nishiura, Inaba (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 #> . #> #> [[57]] #> Nishiura, Inaba (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 #> . #> #> [[58]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[59]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[60]] #> Tuite, etal (2010). “Estimated epidemiologic parameters and morbidity #> associated with pandemic H1N1 influenza.” _Canadian Medical Association #> Journal_. doi:10.1503/cmaj.091807 #> . #> #> [[61]] #> Virlogeux, etal (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 #> . #> #> [[62]] #> Virlogeux, etal (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 #> . #> #> [[63]] #> Virlogeux, etal (2016). “Association between the Severity of Influenza #> A(H7N9) Virus Infections and Length of the Incubation Period.” _PLoS #> One_. doi:10.1371/journal.pone.0148506 #> . #> #> [[64]] #> Virlogeux, etal (2016). “Association between the Severity of Influenza #> A(H7N9) Virus Infections and Length of the Incubation Period.” _PLoS #> One_. doi:10.1371/journal.pone.0148506 #> . #> #> [[65]] #> Virlogeux, etal (2016). “Association between the Severity of Influenza #> A(H7N9) Virus Infections and Length of the Incubation Period.” _PLoS #> One_. doi:10.1371/journal.pone.0148506 #> . #> #> [[66]] #> Ghani, etal (2009). “The Early Transmission Dynamics of H1N1pdm #> Influenza in the United Kingdom.” _PLoS Currents_. #> doi:10.1371/currents.RRN1130 #> . #> #> [[67]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[68]] #> Pavlin (2014). “Calculation of incubation period and serial interval #> from multiple outbreaks of Marburg virus disease.” _BMC Research #> Notes_. doi:10.1186/1756-0500-7-906 #> . #> #> [[69]] #> Pavlin (2014). “Calculation of incubation period and serial interval #> from multiple outbreaks of Marburg virus disease.” _BMC Research #> Notes_. doi:10.1186/1756-0500-7-906 #> . #> #> [[70]] #> Colebunders (2007). “Marburg hemorrhagic fever in Durba and Watsa, #> Democratic Republic of the Congo: clinical documentation, features of #> illness, and treatment.” _The Journal of Infectious Diseases_. #> doi:10.1086/520543 . #> #> [[71]] #> Ajelli, Merler (2012). “Transmission Potential and Design of Adequate #> Control Measures for Marburg Hemorrhagic Fever.” _PLoS One_. #> doi:10.1371/journal.pone.0050948 #> . #> #> [[72]] #> Pavlin (2014). “Calculation of incubation period and serial interval #> from multiple outbreaks of Marburg virus disease.” _BMC Research #> Notes_. doi:10.1186/1756-0500-7-906 #> . #> #> [[73]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-12 #> . #> #> [[74]] #> Assiri, etal (2013). “Hospital Outbreak of Middle East Respiratory #> Syndrome Coronavirus.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa1306742 . #> #> [[75]] #> Cowling, etal (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 #> . #> #> [[76]] #> Assiri, etal (2013). “Hospital Outbreak of Middle East Respiratory #> Syndrome Coronavirus.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa1306742 . #> #> [[77]] #> Mizumoto, etal (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 #> . #> #> [[78]] #> Assiri, etal (2013). “Hospital Outbreak of Middle East Respiratory #> Syndrome Coronavirus.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa1306742 . #> #> [[79]] #> Assiri, etal (2013). “Hospital Outbreak of Middle East Respiratory #> Syndrome Coronavirus.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa1306742 . #> #> [[80]] #> Assiri, etal (2013). “Hospital Outbreak of Middle East Respiratory #> Syndrome Coronavirus.” _The New England Journal of Medicine_. #> doi:10.1056/NEJMoa1306742 . #> #> [[81]] #> Cowling, etal (2015). “Preliminary epidemiological assessment of #> MERS-CoV outbreak in South Korea, May to June 2016.” #> _Eurosurveillance_. doi:10.2807/1560-7917.es2015.20.25.21163 #> . #> #> [[82]] #> Charniga, etal (2022). “Estimating the incubation period of monkeypox #> virus during the 2022 multi-national outbreak.” _medRxiv_. #> doi:10.1101/2022.06.22.22276713 #> . #> #> [[83]] #> Guzetta, etal (2022). “Early Estimates of Monkeypox Incubation Period, #> Generation Time, and Reproduction Number, Italy, May-June 2022.” #> _Emerging Infectious Diseases_. doi:10.3201/eid2810.221126 #> . #> #> [[84]] #> Madewell, etal (2022). “Serial interval and incubation period estimates #> of monkeypox virus infection in 12 U.S. jurisdictions, May – August #> 2022.” _medRxiv_. doi:10.1101/2022.10.26.22281516 #> . #> #> [[85]] #> Madewell, etal (2022). “Serial interval and incubation period estimates #> of monkeypox virus infection in 12 U.S. jurisdictions, May – August #> 2023.” _medRxiv_. doi:10.1101/2022.10.26.22281517 #> . #> #> [[86]] #> Miura, etal (2022). “Estimated incubation period for monkeypox cases #> confirmed in the Netherlands, May 2022.” _Eurosurveillance_. #> doi:10.2807/1560-7917.ES.2022.27.24.2200448 #> . #> #> [[87]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac107 . #> #> [[88]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac108 . #> #> [[89]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac109 . #> #> [[90]] #> Wei, etal (2022). “Study and prediction of the 2022 global monkeypox #> epidemic.” _Journal of Biosafety and Biosecurity_. #> doi:10.1016/j.jobb.2022.12.001 #> . #> #> [[91]] #> Wei, etal (2022). “Study and prediction of the 2022 global monkeypox #> epidemic.” _Journal of Biosafety and Biosecurity_. #> doi:10.1016/j.jobb.2022.12.002 #> . #> #> [[92]] #> Wei, etal (2022). “Study and prediction of the 2022 global monkeypox #> epidemic.” _Journal of Biosafety and Biosecurity_. #> doi:10.1016/j.jobb.2022.12.003 #> . #> #> [[93]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[94]] #> Guo, etal (2022). “Estimation of the serial interval of monkeypox #> during the early outbreak in 2022.” _Journal of Medical Virology_. #> doi:10.1002/jmv.28248 . #> #> [[95]] #> Madewell, etal (2022). “Serial interval and incubation period estimates #> of monkeypox virus infection in 12 U.S. jurisdictions, May – August #> 2024.” _medRxiv_. doi:10.1101/2022.10.26.22281518 #> . #> #> [[96]] #> Madewell, etal (2022). “Serial interval and incubation period estimates #> of monkeypox virus infection in 12 U.S. jurisdictions, May – August #> 2025.” _medRxiv_. doi:10.1101/2022.10.26.22281519 #> . #> #> [[97]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac105 . #> #> [[98]] #> Wang, etal (2022). “Serial intervals and incubation periods of the #> monkeypox virus clades.” _Journal of Travel Medicine_. #> doi:10.1093/jtm/taac106 . #> #> [[99]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-13 #> . #> #> [[100]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[101]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-15 #> . #> #> [[102]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[103]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-14 #> . #> #> [[104]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[105]] #> Reich, etal (2009). “Estimating incubation period distributions with #> coarse data.” _Statistics in Medicine_. doi:10.1002/sim.3659 #> . #> #> [[106]] #> Lessler, etal (2009). “Incubation periods of acute respiratory viral #> infections: a systematic review.” _The Lancet Infectious Diseases_. #> doi:10.1016/S1473-3099(09)70069-8 #> . #> #> [[107]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[108]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[109]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[110]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[111]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[112]] #> Lloyd-Smith, etal (2005). “Superspreading and the effect of individual #> variation on disease emergence.” _Nature_. doi:10.1038/nature04153 #> . #> #> [[113]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[114]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[115]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[116]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[117]] #> Rudolph, etal (2014). “Incubation periods of mosquito-borne viral #> infections: a systematic review.” _The American Journal of Tropical #> Medicine and Hygiene_. doi:10.4269/ajtmh.13-0403 #> . #> #> [[118]] #> Lessler, etal (2016). “Times to key events in Zika virus infection and #> implications for blood donation: a systematic review.” _Bulletin of the #> World Health Organization_. doi:10.2471/BLT.16.174540 #> . #>"},{"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 \"q_\" followed value. 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(q_5 = 1, q_95 = 10)) # 95th interval get_percentiles(c(q_2.5 = 1, q_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/head.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"head() and tail() methods for class — head.epiparam","title":"head() and tail() methods for class — head.epiparam","text":"head() tail() methods class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"head() and tail() methods for class — head.epiparam","text":"","code":"# S3 method for epiparam head(x, ...) # S3 method for epiparam tail(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"head() and tail() methods for class — head.epiparam","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"head() and tail() methods for class — head.epiparam","text":"Data frame","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/head.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"head() and tail() methods for class — head.epiparam","text":"","code":"head(epiparam()) #> disease pathogen epi_distribution author #> 1 Adenovirus Adenovirus incubation_period Lessler_etal #> 2 Chikungunya Chikungunya Virus incubation_period Rudolph_etal #> 3 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 4 COVID-19 SARS-CoV-2 hospitalisation_to_death Linton_etal #> 5 COVID-19 SARS-CoV-2 incubation_period Alene_etal #> 6 COVID-19 SARS-CoV-2 incubation_period Bui_etal #> title #> 1 Incubation periods of acute respiratory viral infections: a systematic review #> 2 Incubation periods of mosquito-borne viral infections: a systematic review #> 3 Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data #> 4 Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data #> 5 Serial interval and incubation period of COVID-19: a systematic review and meta-analysis #> 6 Estimation of the incubation period of COVID-19 in Vietnam #> journal year sample_size #> 1 The Lancet Infectious Diseases 2009 14 #> 2 The American Journal of Tropical Medicine and Hygiene 2014 21 #> 3 Journal of Clinical Medicine 2020 39 #> 4 Journal of Clinical Medicine 2020 39 #> 5 BMC Infectious Diseases 2021 1453 #> 6 PLoS One 2020 19 #> region transmission_mode vector extrinsic #> 1 USA experimental FALSE #> 2 Mixed vector_borne Aedes albopictus FALSE #> 3 China natural_human_to_human FALSE #> 4 China natural_human_to_human FALSE #> 5 Mixed natural_natural_human_to_human FALSE #> 6 Vietnam natural_natural_human_to_human FALSE #> prob_distribution inference_method mean mean_ci_limits mean_ci sd #> 1 lnorm mle NA NA, NA NA NA #> 2 lnorm mle NA NA, NA NA NA #> 3 weibull bayesian 8.9 7.3, 10.4 95 5.70 #> 4 lnorm bayesian 13.0 8.7, 20.9 95 12.70 #> 5 6.5 5.9, 7.1 95 NA #> 6 weibull bayesian 6.4 4.89, 8.50 95 3.05 #> sd_ci_limits sd_ci quantile_2.5 quantile_5 quantile_25 median #> 1 NA, NA NA NA NA 4.8 5.6 #> 2 NA, NA NA NA NA 2.9 3.0 #> 3 4.3, 7.8 95 NA 1.7 NA 8.0 #> 4 6.4, 26.0 95 NA 2.5 NA 9.1 #> 5 NA, NA NA NA NA NA NA #> 6 3.05, 5.30 95 1.35 1.9 NA 6.1 #> median_ci_limits median_ci quantile_75 quantile_87.5 quantile_95 #> 1 4.8, 6.3 95 6.5 NA NA #> 2 0.5, 3.1 95 3.0 NA NA #> 3 6.2, 9.8 95 NA NA 18.8 #> 4 6.7, 13.7 95 NA NA 33.1 #> 5 NA, NA NA NA NA NA #> 6 NA, NA NA NA NA 11.9 #> quantile_97.5 lower_range upper_range shape shape_ci_limits shape_ci scale #> 1 NA NA NA NA NA, NA NA NA #> 2 NA NA NA NA NA, NA NA NA #> 3 NA NA NA NA NA, NA NA NA #> 4 NA NA NA NA NA, NA NA NA #> 5 NA NA NA NA NA, NA NA NA #> 6 13.04 NA NA NA NA, NA NA NA #> scale_ci_limits scale_ci meanlog meanlog_ci_limits meanlog_ci sdlog #> 1 NA, NA NA NA NA, NA NA NA #> 2 NA, NA NA NA NA, NA NA NA #> 3 NA, NA NA NA NA, NA NA NA #> 4 NA, NA NA NA NA, NA NA NA #> 5 NA, NA NA NA NA, NA NA NA #> 6 NA, NA NA NA NA, NA NA NA #> sdlog_ci_limits sdlog_ci dispersion dispersion_ci_limits dispersion_ci #> 1 NA, NA NA 1.26 1.13, 1.38 95 #> 2 NA, NA NA 1.04 1.04, 1.08 95 #> 3 NA, NA NA NA NA, NA NA #> 4 NA, NA NA NA NA, NA NA #> 5 NA, NA NA NA NA, NA NA #> 6 NA, NA NA NA NA, NA NA #> precision precision_ci_limits precision_ci truncation discretised censored #> 1 NA NA, NA NA NA FALSE TRUE #> 2 NA NA, NA NA NA FALSE TRUE #> 3 NA NA, NA NA NA FALSE TRUE #> 4 NA NA, NA NA NA FALSE TRUE #> 5 NA NA, NA NA NA FALSE FALSE #> 6 NA NA, NA NA NA FALSE TRUE #> right_truncated phase_bias_adjusted #> 1 FALSE FALSE #> 2 FALSE FALSE #> 3 FALSE FALSE #> 4 TRUE TRUE #> 5 FALSE FALSE #> 6 FALSE FALSE #> notes #> 1 Analysis on data from Commission on Acute Respiratory Disease. Experimental transmission of minor respiratory illness to human volunteers by filter-passing agents. I. Demonstration of two types of illness characterized by long and short incubation periods and diff erent clinical features. J Clin Invest 1947; 26: 957–82. #> 2 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets #> 3 This method does not apply right-truncation, but does compare the gamma, weibull and lognormal distributions. #> 4 This method applies right-truncation but only fits a lognormal distribution. #> 5 This estimated mean incubation period is from a meta-analysis of 14 other incubation period estimates. Only the mean is reported and a distribution cannot be specified as the meta-mean is estimated from a random-effects model. #> 6 No additional notes #> PMID DOI #> 1 19393959 10.1016/S1473-3099(09)70069-6 #> 2 24639305 10.4269/ajtmh.13-0403 #> 3 32079150 10.3390/jcm9020538 #> 4 32079150 10.3390/jcm9020538 #> 5 33706702 10.1186/s12879-021-05950-x #> 6 33362233 10.1371/journal.pone.0243889 tail(epiparam()) #> disease pathogen epi_distribution author #> 113 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 114 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 115 West Nile Fever West Nile Virus incubation_period Rudolph_etal #> 116 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 117 Yellow Fever Yellow Fever Viruses incubation_period Rudolph_etal #> 118 Zika Virus Disease Zika Virus incubation_period Lessler_etal #> title #> 113 Incubation periods of mosquito-borne viral infections: a systematic review #> 114 Incubation periods of mosquito-borne viral infections: a systematic review #> 115 Incubation periods of mosquito-borne viral infections: a systematic review #> 116 Incubation periods of mosquito-borne viral infections: a systematic review #> 117 Incubation periods of mosquito-borne viral infections: a systematic review #> 118 Times to key events in Zika virus infection and implications for blood donation: a systematic review #> journal year sample_size #> 113 The American Journal of Tropical Medicine and Hygiene 2014 18 #> 114 The American Journal of Tropical Medicine and Hygiene 2014 8 #> 115 The American Journal of Tropical Medicine and Hygiene 2014 6 #> 116 The American Journal of Tropical Medicine and Hygiene 2014 91 #> 117 The American Journal of Tropical Medicine and Hygiene 2014 80 #> 118 Bulletin of the World Health Organization 2016 25 #> region transmission_mode vector extrinsic #> 113 Mixed multiple FALSE #> 114 Mixed vector_borne mosquito FALSE #> 115 Mixed organ_transplant FALSE #> 116 Mixed multiple FALSE #> 117 Mixed vector_borne mosquito FALSE #> 118 Mixed vector_borne Aedes aegypti and Aedes albopictus FALSE #> prob_distribution inference_method mean mean_ci_limits mean_ci sd #> 113 lnorm mle NA NA, NA NA NA #> 114 lnorm mle NA NA, NA NA NA #> 115 lnorm mle NA NA, NA NA NA #> 116 lnorm mle NA NA, NA NA NA #> 117 lnorm mle NA NA, NA NA NA #> 118 lnorm bayesian NA NA, NA NA NA #> sd_ci_limits sd_ci quantile_2.5 quantile_5 quantile_25 median #> 113 NA, NA NA NA 1.0 1.7 2.6 #> 114 NA, NA NA NA NA 2.8 2.9 #> 115 NA, NA NA NA NA 8.7 10.8 #> 116 NA, NA NA NA 1.9 3.2 4.4 #> 117 NA, NA NA NA 1.9 3.1 4.4 #> 118 NA, NA NA NA 3.2 4.6 5.9 #> median_ci_limits median_ci quantile_75 quantile_87.5 quantile_95 #> 113 1.6, 3.5 95 3.8 NA 7.0 #> 114 0.5, 3.1 95 3.0 NA NA #> 115 8.4, 14.2 95 13.3 NA NA #> 116 4, 5 95 6.3 NA 10.3 #> 117 3.9, 5.0 95 6.2 NA 10.3 #> 118 4.4, 7.6 95 7.6 NA 11.2 #> quantile_97.5 lower_range upper_range shape shape_ci_limits shape_ci scale #> 113 NA NA NA NA NA, NA NA NA #> 114 NA NA NA NA NA, NA NA NA #> 115 NA NA NA NA NA, NA NA NA #> 116 NA NA NA NA NA, NA NA NA #> 117 NA NA NA NA NA, NA NA NA #> 118 NA NA NA NA NA, NA NA NA #> scale_ci_limits scale_ci meanlog meanlog_ci_limits meanlog_ci sdlog #> 113 NA, NA NA NA NA, NA NA NA #> 114 NA, NA NA NA NA, NA NA NA #> 115 NA, NA NA NA NA, NA NA NA #> 116 NA, NA NA NA NA, NA NA NA #> 117 NA, NA NA NA NA, NA NA NA #> 118 NA, NA NA NA NA, NA NA NA #> sdlog_ci_limits sdlog_ci dispersion dispersion_ci_limits dispersion_ci #> 113 NA, NA NA 1.82 1.27, 2.67 95 #> 114 NA, NA NA 1.04 1.04, 1.29 95 #> 115 NA, NA NA 1.35 1.12, 1.47 95 #> 116 NA, NA NA 1.66 1.48, 1.82 95 #> 117 NA, NA NA 1.67 1.47, 1.84 95 #> 118 NA, NA NA 1.50 1.2, 1.9 95 #> precision precision_ci_limits precision_ci truncation discretised censored #> 113 NA NA, NA NA NA FALSE TRUE #> 114 NA NA, NA NA NA FALSE TRUE #> 115 NA NA, NA NA NA FALSE TRUE #> 116 NA NA, NA NA NA FALSE TRUE #> 117 NA NA, NA NA NA FALSE TRUE #> 118 NA NA, NA NA NA FALSE TRUE #> right_truncated phase_bias_adjusted #> 113 FALSE FALSE #> 114 FALSE FALSE #> 115 FALSE FALSE #> 116 FALSE FALSE #> 117 FALSE FALSE #> 118 FALSE FALSE #> notes #> 113 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets #> 114 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets. This is a subset of data containing only mosquito-transmitted infections #> 115 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets. This is a subset of data containing only tramsission by transplant or transfusion. #> 116 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets #> 117 Pooled analysis on several data sets, see Rudolph et al 2014 for references of datasets. This is a subset of data containing only mosquito-transmitted infections #> 118 Pooled analysis on several data sets, see Lessler et al. 2016 for references of datasets #> PMID DOI #> 113 24639305 10.4269/ajtmh.13-0403 #> 114 24639305 10.4269/ajtmh.13-0403 #> 115 24639305 10.4269/ajtmh.13-0403 #> 116 24639305 10.4269/ajtmh.13-0403 #> 117 24639305 10.4269/ajtmh.13-0403 #> 118 27821887 10.2471/BLT.16.174540"},{"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_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_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_params = c(shape = 2, scale = 1)) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Check object is an — is_epiparam","title":"Check object is an — is_epiparam","text":"Check object ","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check object is an — is_epiparam","text":"","code":"is_epiparam(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check object is an — is_epiparam","text":"x R object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check object is an — is_epiparam","text":"boolean logical, TRUE object FALSE .","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check object is an — is_epiparam","text":"","code":"eparam <- epiparam() is_epiparam(eparam) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if or object contain a distribution and\ndistribution parameters — is_parameterised","title":"Check if or object contain a distribution and\ndistribution parameters — is_parameterised","text":"Check object contain 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 object contain a distribution and\ndistribution parameters — is_parameterised","text":"","code":"is_parameterised(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/is_parameterised.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if or object contain a distribution and\ndistribution parameters — is_parameterised","text":"x object. ... 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 object contain a distribution and\ndistribution parameters — is_parameterised","text":"single boolean logical vector boolean logicals length equal number rows . object row 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 object contain a distribution and\ndistribution 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 #> Unparameterised object is_parameterised(edist) #> [1] 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 an epiparam object — list_distributions","title":"List epidemiological distributions stored in an epiparam object — list_distributions","text":"function subsets epiparam object return chosen epidemiological distribution. results returned data frame better see returned distributions. default resulting data frame subset return disease, epidemiological distribution, probability distribution, author study year publication well sample size study. columns database required set subset_db = FALSE.","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 an epiparam object — list_distributions","text":"","code":"list_distributions( epiparam, epi_dist = c(\"incubation_period\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\", \"generation_time\", \"offspring_distribution\"), subset_db = TRUE )"},{"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 an epiparam object — list_distributions","text":"epiparam object. epi_dist character defining parameter listed: \"incubation\", \"onset_to_hospitalisation\", \"onset_to_death\", \"serial_interval\". \"incubation_period\" default epi_dist epi_dist specified incubation periods returned. subset_db boolean logical determines whether subset, defaults TRUE.","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 an epiparam object — list_distributions","text":"Adam Kucharski, Joshua W. Lambert","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 an epiparam object — list_distributions","text":"","code":"eparam <- epiparam() list_distributions(epiparam = eparam, epi_dist = \"incubation_period\") #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 incubation_period #> 4 COVID-19 incubation_period weibull #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period lnorm #> 7 COVID-19 incubation_period lnorm #> 8 COVID-19 incubation_period lnorm #> 9 COVID-19 incubation_period lnorm #> 10 COVID-19 incubation_period lnorm #> 11 COVID-19 incubation_period lnorm #> 12 COVID-19 incubation_period lnorm #> 13 COVID-19 incubation_period lnorm #> 14 COVID-19 incubation_period lnorm #> 15 COVID-19 incubation_period #> 16 COVID-19 incubation_period #> 17 Dengue incubation_period lnorm #> 18 Dengue incubation_period lnorm #> 19 Dengue incubation_period lnorm #> 20 Dengue incubation_period lnorm #> 21 Dengue incubation_period lnorm #> 22 Ebola Virus Disease incubation_period lnorm #> 23 Ebola Virus Disease incubation_period gamma #> 24 Ebola Virus Disease incubation_period gamma #> 25 Ebola Virus Disease incubation_period gamma #> 26 Ebola Virus Disease incubation_period gamma #> 27 Human Coronavirus incubation_period lnorm #> 28 Influenza incubation_period gamma #> 29 Influenza incubation_period lnorm #> 30 Influenza incubation_period lnorm #> 31 Influenza incubation_period lnorm #> 32 Influenza incubation_period lnorm #> 33 Influenza incubation_period gamma #> 34 Influenza incubation_period weibull #> 35 Influenza incubation_period lnorm #> 36 Influenza incubation_period lnorm #> 37 Influenza incubation_period lnorm #> 38 Influenza incubation_period weibull #> 39 Influenza incubation_period gamma #> 40 Influenza incubation_period weibull #> 41 Influenza incubation_period weibull #> 42 Influenza incubation_period weibull #> 43 Japanese Encephalitis incubation_period lnorm #> 44 Marburg Virus Disease incubation_period #> 45 Marburg Virus Disease incubation_period #> 46 Measles incubation_period lnorm #> 47 MERS incubation_period lnorm #> 48 MERS incubation_period gamma #> 49 Mpox incubation_period lnorm #> 50 Mpox incubation_period gamma #> 51 Mpox incubation_period lnorm #> 52 Mpox incubation_period lnorm #> 53 Mpox incubation_period lnorm #> 54 Mpox incubation_period #> 55 Mpox incubation_period #> 56 Mpox incubation_period #> 57 Mpox incubation_period #> 58 Mpox incubation_period #> 59 Mpox incubation_period #> 60 Parainfluenza incubation_period lnorm #> 61 Rhinovirus incubation_period lnorm #> 62 Rift Valley Fever incubation_period lnorm #> 63 RSV incubation_period lnorm #> 64 RSV incubation_period lnorm #> 65 RSV incubation_period lnorm #> 66 SARS incubation_period lnorm #> 67 West Nile Fever incubation_period lnorm #> 68 West Nile Fever incubation_period lnorm #> 69 West Nile Fever incubation_period lnorm #> 70 Yellow Fever incubation_period lnorm #> 71 Yellow Fever incubation_period lnorm #> 72 Zika Virus Disease incubation_period lnorm #> author year sample_size #> 1 Lessler_etal 2009 14 #> 2 Rudolph_etal 2014 21 #> 3 Alene_etal 2021 1453 #> 4 Bui_etal 2020 19 #> 5 Elias_etal 2021 28675 #> 6 Lauer_etal 2020 181 #> 7 Lauer_etal 2020 99 #> 8 Lauer_etal 2020 108 #> 9 Lauer_etal 2020 73 #> 10 Linton_etal 2020 52 #> 11 Linton_etal 2020 158 #> 12 Linton_etal 2020 52 #> 13 McAloon_etal 2020 1357 #> 14 McAloon_etal 2020 1269 #> 15 Men_etal 2020 59 #> 16 Rai_etal 2022 6241 #> 17 Chan_Johansson 2012 146 #> 18 Chan_Johansson 2012 146 #> 19 Chan_Johansson 2012 153 #> 20 Rudolph_etal 2014 169 #> 21 Rudolph_etal 2014 124 #> 22 Eichner_etal 2011 196 #> 23 WHO_Ebola_Response_Team 2015 49 #> 24 WHO_Ebola_Response_Team 2015 957 #> 25 WHO_Ebola_Response_Team 2015 792 #> 26 WHO_Ebola_ResponseTeam 2015 1798 #> 27 Lessler_etal 2009 13 #> 28 Ghani_etal 2009 16 #> 29 Lessler_etal 2009 151 #> 30 Lessler_etal 2009 90 #> 31 Lessler_etal 2009 78 #> 32 Lessler_etal 2009 124 #> 33 Nishiura_Inaba 2011 72 #> 34 Nishiura_Inaba 2011 72 #> 35 Reich_etal 2009 151 #> 36 Reich_etal 2009 151 #> 37 Tuite_etal 2010 316 #> 38 Virlogeux_etal 2015 229 #> 39 Virlogeux_etal 2015 229 #> 40 Virlogeux_etal 2016 395 #> 41 Virlogeux_etal 2016 173 #> 42 Virlogeux_etal 2016 222 #> 43 Rudolph_etal 2014 6 #> 44 Pavlin 2014 76 #> 45 Pavlin 2014 18 #> 46 Lessler_etal 2009 55 #> 47 Assiri_etal 2013 23 #> 48 Cowling_etal 2015 166 #> 49 Charniga_etal 2022 22 #> 50 Guzetta_etal 2022 255 #> 51 Madewell_etal 2022 35 #> 52 Madewell_etal 2022 36 #> 53 Miura_etal 2022 18 #> 54 Wang_etal 2022 16 #> 55 Wang_etal 2022 27 #> 56 Wang_etal 2022 114 #> 57 Wei_etal 2022 NA #> 58 Wei_etal 2022 NA #> 59 Wei_etal 2022 NA #> 60 Lessler_etal 2009 11 #> 61 Lessler_etal 2009 28 #> 62 Rudolph_etal 2014 23 #> 63 Lessler_etal 2009 24 #> 64 Reich_etal 2009 24 #> 65 Reich_etal 2009 24 #> 66 Lessler_etal 2009 157 #> 67 Rudolph_etal 2014 18 #> 68 Rudolph_etal 2014 8 #> 69 Rudolph_etal 2014 6 #> 70 Rudolph_etal 2014 91 #> 71 Rudolph_etal 2014 80 #> 72 Lessler_etal 2016 25 # the default for list_distributions() without any arguments is to return the # incubation period list_distributions(epiparam = eparam) #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 incubation_period #> 4 COVID-19 incubation_period weibull #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period lnorm #> 7 COVID-19 incubation_period lnorm #> 8 COVID-19 incubation_period lnorm #> 9 COVID-19 incubation_period lnorm #> 10 COVID-19 incubation_period lnorm #> 11 COVID-19 incubation_period lnorm #> 12 COVID-19 incubation_period lnorm #> 13 COVID-19 incubation_period lnorm #> 14 COVID-19 incubation_period lnorm #> 15 COVID-19 incubation_period #> 16 COVID-19 incubation_period #> 17 Dengue incubation_period lnorm #> 18 Dengue incubation_period lnorm #> 19 Dengue incubation_period lnorm #> 20 Dengue incubation_period lnorm #> 21 Dengue incubation_period lnorm #> 22 Ebola Virus Disease incubation_period lnorm #> 23 Ebola Virus Disease incubation_period gamma #> 24 Ebola Virus Disease incubation_period gamma #> 25 Ebola Virus Disease incubation_period gamma #> 26 Ebola Virus Disease incubation_period gamma #> 27 Human Coronavirus incubation_period lnorm #> 28 Influenza incubation_period gamma #> 29 Influenza incubation_period lnorm #> 30 Influenza incubation_period lnorm #> 31 Influenza incubation_period lnorm #> 32 Influenza incubation_period lnorm #> 33 Influenza incubation_period gamma #> 34 Influenza incubation_period weibull #> 35 Influenza incubation_period lnorm #> 36 Influenza incubation_period lnorm #> 37 Influenza incubation_period lnorm #> 38 Influenza incubation_period weibull #> 39 Influenza incubation_period gamma #> 40 Influenza incubation_period weibull #> 41 Influenza incubation_period weibull #> 42 Influenza incubation_period weibull #> 43 Japanese Encephalitis incubation_period lnorm #> 44 Marburg Virus Disease incubation_period #> 45 Marburg Virus Disease incubation_period #> 46 Measles incubation_period lnorm #> 47 MERS incubation_period lnorm #> 48 MERS incubation_period gamma #> 49 Mpox incubation_period lnorm #> 50 Mpox incubation_period gamma #> 51 Mpox incubation_period lnorm #> 52 Mpox incubation_period lnorm #> 53 Mpox incubation_period lnorm #> 54 Mpox incubation_period #> 55 Mpox incubation_period #> 56 Mpox incubation_period #> 57 Mpox incubation_period #> 58 Mpox incubation_period #> 59 Mpox incubation_period #> 60 Parainfluenza incubation_period lnorm #> 61 Rhinovirus incubation_period lnorm #> 62 Rift Valley Fever incubation_period lnorm #> 63 RSV incubation_period lnorm #> 64 RSV incubation_period lnorm #> 65 RSV incubation_period lnorm #> 66 SARS incubation_period lnorm #> 67 West Nile Fever incubation_period lnorm #> 68 West Nile Fever incubation_period lnorm #> 69 West Nile Fever incubation_period lnorm #> 70 Yellow Fever incubation_period lnorm #> 71 Yellow Fever incubation_period lnorm #> 72 Zika Virus Disease incubation_period lnorm #> author year sample_size #> 1 Lessler_etal 2009 14 #> 2 Rudolph_etal 2014 21 #> 3 Alene_etal 2021 1453 #> 4 Bui_etal 2020 19 #> 5 Elias_etal 2021 28675 #> 6 Lauer_etal 2020 181 #> 7 Lauer_etal 2020 99 #> 8 Lauer_etal 2020 108 #> 9 Lauer_etal 2020 73 #> 10 Linton_etal 2020 52 #> 11 Linton_etal 2020 158 #> 12 Linton_etal 2020 52 #> 13 McAloon_etal 2020 1357 #> 14 McAloon_etal 2020 1269 #> 15 Men_etal 2020 59 #> 16 Rai_etal 2022 6241 #> 17 Chan_Johansson 2012 146 #> 18 Chan_Johansson 2012 146 #> 19 Chan_Johansson 2012 153 #> 20 Rudolph_etal 2014 169 #> 21 Rudolph_etal 2014 124 #> 22 Eichner_etal 2011 196 #> 23 WHO_Ebola_Response_Team 2015 49 #> 24 WHO_Ebola_Response_Team 2015 957 #> 25 WHO_Ebola_Response_Team 2015 792 #> 26 WHO_Ebola_ResponseTeam 2015 1798 #> 27 Lessler_etal 2009 13 #> 28 Ghani_etal 2009 16 #> 29 Lessler_etal 2009 151 #> 30 Lessler_etal 2009 90 #> 31 Lessler_etal 2009 78 #> 32 Lessler_etal 2009 124 #> 33 Nishiura_Inaba 2011 72 #> 34 Nishiura_Inaba 2011 72 #> 35 Reich_etal 2009 151 #> 36 Reich_etal 2009 151 #> 37 Tuite_etal 2010 316 #> 38 Virlogeux_etal 2015 229 #> 39 Virlogeux_etal 2015 229 #> 40 Virlogeux_etal 2016 395 #> 41 Virlogeux_etal 2016 173 #> 42 Virlogeux_etal 2016 222 #> 43 Rudolph_etal 2014 6 #> 44 Pavlin 2014 76 #> 45 Pavlin 2014 18 #> 46 Lessler_etal 2009 55 #> 47 Assiri_etal 2013 23 #> 48 Cowling_etal 2015 166 #> 49 Charniga_etal 2022 22 #> 50 Guzetta_etal 2022 255 #> 51 Madewell_etal 2022 35 #> 52 Madewell_etal 2022 36 #> 53 Miura_etal 2022 18 #> 54 Wang_etal 2022 16 #> 55 Wang_etal 2022 27 #> 56 Wang_etal 2022 114 #> 57 Wei_etal 2022 NA #> 58 Wei_etal 2022 NA #> 59 Wei_etal 2022 NA #> 60 Lessler_etal 2009 11 #> 61 Lessler_etal 2009 28 #> 62 Rudolph_etal 2014 23 #> 63 Lessler_etal 2009 24 #> 64 Reich_etal 2009 24 #> 65 Reich_etal 2009 24 #> 66 Lessler_etal 2009 157 #> 67 Rudolph_etal 2014 18 #> 68 Rudolph_etal 2014 8 #> 69 Rudolph_etal 2014 6 #> 70 Rudolph_etal 2014 91 #> 71 Rudolph_etal 2014 80 #> 72 Lessler_etal 2016 25 # this same process can be achieved when loading the library eparam <- epiparam(epi_dist = \"incubation_period\") # filtering for onset to death list_distributions(epiparam = eparam, epi_dist = \"onset_to_death\") #> [1] disease epi_distribution prob_distribution author #> [5] year sample_size #> <0 rows> (or 0-length row.names)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an object from a list of input from an\n object — make_epidist","title":"Create an object from a list of input from an\n object — make_epidist","text":"Unpacks list inputs object helper, including parameters uncertainty correct type probability distribution.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an object from a list of input from an\n object — make_epidist","text":"","code":"make_epidist(x)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an object from a list of input from an\n object — make_epidist","text":"x List data used construct object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/make_epidist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an object from a list of input from an\n object — make_epidist","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Set names for class — names<-.epiparam","title":"Set names for class — names<-.epiparam","text":"modifying names invalidates object (defined invariants, encoded validate_epiparam()) subsetting return data frame message console stating class object converted data frame attributes class preserved.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set names for class — names<-.epiparam","text":"","code":"# S3 method for epiparam names(x) <- value"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set names for class — names<-.epiparam","text":"x R object. value character vector length x, NULL.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/names-set-.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set names for class — names<-.epiparam","text":"epiparam object data.frame","code":""},{"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 wiht 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_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for class — new_epiparam","title":"Constructor for class — new_epiparam","text":"constructor reads data stored internally package subsets epidemiological distribution (epi_dist).","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for class — new_epiparam","text":"","code":"new_epiparam(epi_dist)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for class — new_epiparam","text":"epi_dist character string name epidemiological distribution type.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for class — new_epiparam","text":" object.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/new_epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Constructor for class — new_epiparam","text":"","code":"eparam <- epiparameter:::new_epiparam(\"all\")"},{"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.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Print method for class — print.epiparam","title":"Print method for class — print.epiparam","text":"Print method class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print method for class — print.epiparam","text":"","code":"# S3 method for epiparam print(x, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print method for class — print.epiparam","text":"x object. ... dots Extra arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print method for class — print.epiparam","text":"Invisibly returns . Called side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/print.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print method for class — print.epiparam","text":"","code":"epiparam <- epiparam() epiparam #> Epiparam object #> Number of distributions in library: 118 #> Number of diseases: 23 #> Number of delay distributions: 95 #> Number of offspring distributions: 10 #> Number of studies in library: 57 #> #> disease epi_distribution prob_distribution #> 1 Adenovirus incubation_period lnorm #> 2 Chikungunya incubation_period lnorm #> 3 COVID-19 hospitalisation_to_death weibull #> 4 COVID-19 hospitalisation_to_death lnorm #> 5 COVID-19 incubation_period #> 6 COVID-19 incubation_period weibull #> <112 more rows & 55 more cols not shown>"},{"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( disease = \"ebola\", epi_dist = \"incubation_period\", prob_distribution = \"gamma\", prob_distribution_params = c(shape = 1, scale = 1) ), extrinsic = 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/sub-.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset method for class — [.epiparam","title":"Subset method for class — [.epiparam","text":"subsetting invalidates object (defined invariants, encoded validate_epiparam()) subsetting return data frame message console stating class object converted data.frame attributes class preserved.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/sub-.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset method for class — [.epiparam","text":"","code":"# S3 method for epiparam [(epiparam, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/sub-.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset method for class — [.epiparam","text":"epiparam object. ... arguments passed methods.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/sub-.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset method for class — [.epiparam","text":"epiparam object data.frame","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Summary method for class — summary.epiparam","title":"Summary method for class — summary.epiparam","text":"Summary method class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summary method for class — summary.epiparam","text":"","code":"# S3 method for epiparam summary(object, ...)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summary method for class — summary.epiparam","text":"object object. ... dots used, extra arguments supplied cause warning.","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summary method for class — summary.epiparam","text":"data frame information","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/summary.epiparam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Summary method for class — summary.epiparam","text":"","code":"x <- epiparam() summary(x) #> $num_entries #> [1] 118 #> #> $num_diseases #> [1] 23 #> #> $num_delay_dist #> [1] 95 #> #> $num_offspring_dist #> [1] 10 #> #> $num_studies #> [1] 57 #> #> $num_continuous_distributions #> [1] 118 #> #> $num_discrete_distributions #> [1] 0 #> #> $num_vector_borne_diseases #> [1] 2 #>"},{"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_epiparam.html","id":null,"dir":"Reference","previous_headings":"","what":"Validator for class — validate_epiparam","title":"Validator for class — validate_epiparam","text":"Validator class","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epiparam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validator for class — validate_epiparam","text":"","code":"validate_epiparam(epiparam, reconstruct = FALSE)"},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epiparam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validator for class — validate_epiparam","text":"epiparam object. reconstruct boolean logical determining whether validation class specific. TRUE input object must type (default), FALSE input object can another class, e.g. data frame. argument used reconstruction operations see epiparam_reconstruct().","code":""},{"path":"https://epiverse-trace.github.io/epiparameter/reference/validate_epiparam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validator for class — validate_epiparam","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"}]