Package: BayesPIM 1.0.1

Thomas Klausch

BayesPIM: Bayesian Prevalence-Incidence Mixture Model

Models time-to-event data from interval-censored screening studies. It accounts for latent prevalence at baseline and incorporates misclassification due to imperfect test sensitivity. For usage details, see the package vignette "BayesPIM_intro". Further details can be found in Klausch, Lissenberg-Witte and Coupé (2026) <doi:10.1002/sim.70433>.

Authors:Thomas Klausch [aut, cre]

BayesPIM_1.0.1.tar.gz
BayesPIM_1.0.1.tar.gz(r-4.7-arm64)BayesPIM_1.0.1.tar.gz(r-4.7-x86_64)BayesPIM_1.0.1.tar.gz(r-4.6-arm64)BayesPIM_1.0.1.tar.gz(r-4.6-x86_64)
BayesPIM_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesPIM/json (API)

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

Bug tracker:https://github.com/thomasklausch2/bayespim/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

2.70 score 82 downloads 8 exports 12 dependencies

Last updated from:8a7b496698. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK139
linux-devel-x86_64OK137
source / vignettesOK218
linux-release-arm64OK137
linux-release-x86_64OK136
wasm-releaseOK128

Exports:bayes.2Sbayes.2S_seqgen.datget.IC_2Sget.ppd.2Ssearch.prop.sdsearch.prop.sd_seqtrim.mcmc

Dependencies:actuarcodacodetoolsdoParallelexpintforeachggammaiteratorslatticeMASSmvtnormRcpp

Introduction to BayesPIM

Rendered fromBayesPIM_intro.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2026-05-08
Started: 2025-03-22