MCMCpack: Markov Chain Monte Carlo inR | Zendy

Andrew D. Martin | Zendy; Kevin M. Quinn | Zendy; Jong Hee Park | Zendy

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MCMCpack: Markov Chain Monte Carlo inR

Author(s) -

Andrew D. Martin,

Kevin M. Quinn,

Jong Hee Park

Publication year - 2011

Publication title -

journal of statistical software

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.636

H-Index - 145

ISSN - 1548-7660

DOI - 10.18637/jss.v042.i09

Subject(s) - markov chain monte carlo , computer science , statistical inference , markov chain , bayesian probability , bayesian inference , monte carlo method , algorithm , r package , gibbs sampling , sampling (signal processing) , mathematics , statistics , computational science , artificial intelligence , machine learning , filter (signal processing) , computer vision

We introduce MCMCpack, an R package that contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. In addition to code that can be used to fit commonly used models, MCMCpack also contains some useful utility functions, including some additional density functions and pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization.

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