R2jags: Using R to Run 'JAGS'

Providing wrapper functions to implement Bayesian analysis in JAGS. Some major features include monitoring convergence of a MCMC model using Rubin and Gelman Rhat statistics, automatically running a MCMC model till it converges, and implementing parallel processing of a MCMC model for multiple chains.

Version: 0.5-7
Depends: R (≥ 2.14.0), rjags (≥ 3-3)
Imports: abind, coda (≥ 0.13), graphics, grDevices, methods, R2WinBUGS, parallel, stats, utils
Published: 2015-08-23
Author: Yu-Sung Su, Masanao Yajima,
Maintainer: Yu-Sung Su <suyusung at tsinghua.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
Materials: ChangeLog
In views: Bayesian
CRAN checks: R2jags results


Reference manual: R2jags.pdf
Package source: R2jags_0.5-7.tar.gz
Windows binaries: r-devel: R2jags_0.5-7.zip, r-release: R2jags_0.5-7.zip, r-oldrel: R2jags_0.5-7.zip
OS X El Capitan binaries: r-release: R2jags_0.5-7.tgz
OS X Mavericks binaries: r-oldrel: R2jags_0.5-7.tgz
Old sources: R2jags archive

Reverse dependencies:

Reverse depends: BayesMed, bmeta, CCTpack, IUPS, miscF
Reverse imports: agRee, bamdit, boral, classify, MixSIAR, rjmcmc, SeqFeatR, upmfit
Reverse suggests: AICcmodavg, BCEA, BCEs0, bridgesampling, ftsa, gap, iBUGS, LakeMetabolizer
Reverse enhances: glmmBUGS


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