runjags: an R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS

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  • runjags

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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.
Original languageEnglish
JournalJournal of Statistical Software
Issue number9
Pages (from-to)1-25
Number of pages25
Publication statusPublished - 2016

    Research areas

  • MCMC, Bayesian, graphical models, interface utilities, JAGS, BUGS, R

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