runjags: Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS

User-friendly interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. A JAGS extension module provides additional distributions including the Pareto family of distributions, the DuMouchel prior and the half-Cauchy prior.

Version: 2.0.4-2
Depends: R (≥ 2.14.0)
Imports: parallel, lattice (≥ 0.20-10), coda (≥ 0.17-1), stats, utils
Suggests: rjags, modeest, knitr
Published: 2016-07-25
Author: Matthew Denwood [aut, cre], Martyn Plummer [cph] (Copyright holder of the code in /src/distributions/jags, src/distributions/DPar1.*,, and original copyright holder of some modified code where indicated)
Maintainer: Matthew Denwood <md at>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: JAGS (
Citation: runjags citation info
Materials: README ChangeLog
In views: Bayesian
CRAN checks: runjags results


Reference manual: runjags.pdf
Vignettes: A quick-start guide to running models in JAGS
Using the runjags package
Package source: runjags_2.0.4-2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: runjags_2.0.4-2.tgz
OS X Mavericks binaries: r-oldrel: runjags_2.0.4-2.tgz
Old sources: runjags archive

Reverse dependencies:

Reverse depends: BANOVA, blavaan
Reverse imports: bayescount, IsotopeR, RcmdrPlugin.RMTCJags, TreeBUGS, tRophicPosition
Reverse suggests: metamisc, surveillance


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