swMATH ID: 31621
Software Authors: Goudie, R. J. B., Turner, R. M., De Angelis, D., Thomas, A.
Description: MultiBUGS: A parallel implementation of the BUGS modelling framework for faster Bayesian inference. MultiBUGS implements a simple, automatic algorithm for parallelising Markov chain Monte Carlo (MCMC) algorithms for posterior inference of Bayesian hierarchical models. It builds on the existing algorithms and tools in OpenBUGS, and so is applicable to the broad range of statistical models that can be fitted using BUGS-language software, but automatically parallelises the MCMC algorithm to dramatically speed up computation. This makes modern multi-core computing accessible to applied statisticians, without requiring any experience of parallel programming.
Homepage: https://www.multibugs.org/
Source Code:  https://github.com/MultiBUGS/MultiBUGS
Keywords: jstatsoft.org; BUGS; parallel computing; Markov chain Monte Carlo; Gibbs sampling; Bayesian analysis; hierarchical models; directed acyclic graph
Related Software: R; WinBUGS; JAGS; CODA; rjags; CRAN Task Views; BUGS; Stan; Rcpp; MCMCvis; R2WinBUGS; LaplacesDemon; RStan; BayesPostEst; PyMC; Mcmcpack; jagsUI; nimble; compareMCMCs; colorspace
Cited in: 2 Documents

Standard Articles

1 Publication describing the Software Year
MultiBUGS: A Parallel Implementation of the BUGS Modeling Framework for Faster Bayesian Inference Link
Robert J. B. Goudie, Rebecca M. Turner, Daniela De Angelis, Andrew Thomas

Cited in 1 Field

2 Statistics (62-XX)

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