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: |
2.2.1-7 |
| Depends: |
R (≥ 2.14.0) |
| Imports: |
parallel, lattice (≥ 0.20-10), coda (≥ 0.17-1), stats, utils |
| Suggests: |
rjags (≥ 4-7), modeest, testthat (≥ 3.0.0), knitr, markdown, spelling |
| Published: |
2022-04-15 |
| Author: |
Matthew Denwood [aut, cre],
Martyn Plummer [cph] (Copyright holder of the code in
src/distributions/DPar1.*, configure.ac, R/rjags_functions.R, and
original copyright holder of some modified code where indicated) |
| Maintainer: |
Matthew Denwood <md at sund.ku.dk> |
| BugReports: |
https://github.com/ku-awdc/runjags/issues |
| License: |
GPL-2 |
| URL: |
https://github.com/ku-awdc/runjags |
| NeedsCompilation: |
yes |
| SystemRequirements: |
JAGS >= 4.3.0 (https://mcmc-jags.sourceforge.io/) |
| Language: |
en-GB |
| Citation: |
runjags citation info |
| Materials: |
README ChangeLog INSTALL |
| In views: |
Bayesian |
| CRAN checks: |
runjags results |