Package: prevalence 0.4.1
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:
prevalence_0.4.1.tar.gz
prevalence_0.4.1.zip(r-4.7)prevalence_0.4.1.zip(r-4.6)prevalence_0.4.1.zip(r-4.5)
prevalence_0.4.1.tgz(r-4.6-any)prevalence_0.4.1.tgz(r-4.5-any)
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://brechtdv.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/brechtdv/prevalence/issues
- 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
Last updated from:62876ff82c. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 108 | ||
| source / vignettes | OK | 164 | ||
| linux-release-x86_64 | NOTE | 129 | ||
| macos-release-arm64 | NOTE | 170 | ||
| macos-oldrel-arm64 | NOTE | 186 | ||
| windows-devel | NOTE | 78 | ||
| windows-release | NOTE | 69 | ||
| windows-oldrel | NOTE | 81 | ||
| wasm-release | OK | 111 |
Exports:as.matrixautocorr.plotbetaExpertbetaPERTdefine_priordefine_prior2define_xdensplotgelman.plotplotprintpropCIshowsummarytraceplottruePrevtruePrevMultitruePrevMulti2truePrevPools
