 runjags: An R Package Providing Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGSMatthew J. Denwood Journal of Statistical Software, 2016, vol. 071, issue i09 Abstract: The runjags package provides a set of interface functions to facilitate running Markov chain Monte Carlo models in JAGS from within R. Automated calculation of appropriate convergence and sample length diagnostics, user-friendly access to commonly used graphical outputs and summary statistics, and parallelized methods of running JAGS are provided. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. Automated simulation study functions are implemented to facilitate model performance assessment, as well as drop-k type cross-validation studies, using high performance computing clusters such as those provided by parallel. A module extension for JAGS is also included within runjags, providing the Pareto family of distributions and a series of minimally-informative priors including the DuMouchel and half-Cauchy priors. This paper outlines the primary functions of this package, and gives an illustration of a simulation study to assess the sensitivity of two equivalent model formulations to different prior distributions. Date: 2016-07-26 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:071:i09 Access Statistics for this article Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis More articles in Journal of Statistical Software from Foundation for Open Access Statistics |
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