Package: rjags 4-17

rjags: Bayesian Graphical Models using MCMC

Interface to the JAGS MCMC library.

Authors:Martyn Plummer [aut, cre], Alexey Stukalov [ctb], Matt Denwood [ctb]

rjags_4-17.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rjags/json (API)

# Install 'rjags' in R:
install.packages('rjags', repos = c('https://martynplummer.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • LINE - Linear regression example

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

9.74 score 9 stars 160 packages 5.8k scripts 22k downloads 260 mentions 17 exports 2 dependencies

Last updated from:59ec6d347d. Checks:14 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK93
linux-devel-x86_64OK93
source / vignettesOK180
linux-release-arm64OK80
linux-release-x86_64OK100
macos-release-arm64OK124
macos-release-x86_64OK390
macos-oldrel-arm64OK88
macos-oldrel-x86_64OK451
windows-devel-arm64OK338
windows-devel-x86_64OK130
windows-release-arm64OK334
windows-release-x86_64OK104
windows-oldrel-x86_64OK98
wasm-releaseFAIL82

Exports:adaptcoda.samplesdic.samplesdiffdicjags.modeljags.samplesjags.versionlist.factorieslist.moduleslist.samplersload.moduleparallel.seedsread.bugsdataread.dataread.jagsdataset.factoryunload.module

Dependencies:codalattice

Readme and manuals

Help Manual

Help pageTopics
Bayesian graphical models using MCMCrjags-package rjags
Adaptive phase for JAGS modelsadapt
Generate posterior samples in mcmc.list formatcoda.samples
Advanced control over JAGSlist.factories set.factory
Generate penalized deviance samplesdic dic.samples
Differences in penalized deviancediffdic
Create a JAGS model objectjags.model
Dynamically load JAGS moduleslist.modules load.module unload.module
Functions for manipulating jags model objectscoef.jags list.samplers variable.names.jags
Generate posterior samplesjags.samples
JAGS versionJAGS.version jags.version
Linear regression exampleLINE
Objects for representing MCMC outputas.mcmc.list.mcarray mcarray.object print.mcarray summary.mcarray
Get initial values for parallel RNGsparallel.seeds
Read data files for jags modelsread.bugsdata read.jagsdata
Deprecated Functions in the rjags packageread.data rjags-deprecated
Update jags modelsupdate.jags