Package: prevalence 0.4.1

Brecht Devleesschauwer

prevalence: Tools for Prevalence Assessment Studies

The prevalence package provides Frequentist and Bayesian methods for prevalence assessment studies. IMPORTANT: the truePrev functions in the prevalence package call on JAGS (Just Another Gibbs Sampler), which therefore has to be available on the user's system. JAGS can be downloaded from <https://mcmc-jags.sourceforge.io/>.

Authors:Brecht Devleesschauwer [aut, cre], Paul Torgerson [aut], Johannes Charlier [aut], Bruno Levecke [aut], Nicolas Praet [aut], Sophie Roelandt [aut], Suzanne Smit [aut], Pierre Dorny [aut], Dirk Berkvens [aut], Niko Speybroeck [aut]

prevalence_0.4.1.tar.gz
prevalence_0.4.1.tar.gz(r-4.7-any)prevalence_0.4.1.tar.gz(r-4.6-any)
prevalence_0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
prevalence/json (API)
NEWS

# Install 'prevalence' in R:
install.packages('prevalence', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/brechtdv/prevalence/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

jagscpp

3.80 score 3 stars 52 scripts 338 downloads 8 mentions 19 exports 3 dependencies

Last updated from:500c652408. Checks:2 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE109
source / vignettesOK215
linux-release-x86_64NOTE118
wasm-releaseOK97

Exports:as.matrixautocorr.plotbetaExpertbetaPERTdefine_priordefine_prior2define_xdensplotgelman.plotplotprintpropCIshowsummarytraceplottruePrevtruePrevMultitruePrevMulti2truePrevPools

Dependencies:codalatticerjags

Readme and manuals

Help Manual

Help pageTopics
Tools for prevalence assessment studiesprevalence-package prevalence
Calculate the parameters of a Beta distribution based on expert informationbetaExpert plot.betaExpert print.betaExpert
Calculate the parameters of a Beta-PERT distributionbetaPERT plot.betaPERT print.betaPERT
Methods for Function 'as.matrix' in Package 'prevalence'as.matrix,prev-method as.matrix-methods convert-methods
Definition of 'truePrevMulti' and 'truePrevMulti2' modeldefine_prior define_prior2 define_x
Methods for Function 'plot' in Package 'prevalence'plot,prev,ANY-method plot,prev-method plot-methods
Plotting functions from package 'coda'autocorr.plot,prev-method autocorr.plot-methods densplot,prev-method densplot-methods gelman.plot,prev-method gelman.plot-methods plot-methods-coda traceplot,prev-method traceplot-methods
Class '"prev"'prev-class
Methods for Function 'print' in Package 'prevalence'print,prev-method print-methods
Calculate confidence intervals for prevalences and other proportionspropCI
Methods for Function 'show' in Package 'prevalence'show,prev-method show-methods
Methods for Function 'summary' in Package 'prevalence'summary,prev-method summary-methods
Estimate true prevalence from individuals samplestruePrev
Estimate true prevalence from individuals samples using multiple tests - conditional probability schemetruePrevMulti
Estimate true prevalence from individuals samples using multiple tests - covariance schemetruePrevMulti2
Estimate true prevalence from pooled samplestruePrevPools