A friendly MCMC framework

Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithm in a modular way allowing users to specify automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Most of the methods implemented in this package can be found in Brooks et al. (2011, ISBN 9781420079425). Among the methods included, we have: Haario (2001) Adaptive Metropolis, Vihola (2012) Robust Adaptive Metropolis, and Thawornwattana et al. (2018) Mirror transition kernels.


Reference manual

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0.4-0 by George Vega Yon, 2 months ago


Report a bug at https://github.com/USCbiostats/fmcmc/issues

Browse source code at https://github.com/cran/fmcmc

Authors: George Vega Yon [aut, cre] , Paul Marjoram [ctb, ths] , National Cancer Institute (NCI) [fnd] (Grant Number 5P01CA196569-02) , Fabian Scheipl [rev] (JOSS reviewer ,

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports parallel, coda, stats, methods, MASS, Matrix

Suggests covr, knitr, rmarkdown, mcmc, tinytest, mvtnorm, adaptMCMC

Suggested by ergmito.

See at CRAN