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).
Version: | 0.2-0 |
Depends: | R (≥ 3.3.0) |
Imports: | parallel, coda, stats, methods |
Suggests: | covr, mvtnorm, knitr, rmarkdown, mcmc, tinytest |
Published: | 2019-08-27 |
Author: | George Vega Yon |
Maintainer: | George Vega Yon <g.vegayon at gmail.com> |
BugReports: | https://github.com/USCbiostats/fmcmc/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/USCbiostats/fmcmc |
NeedsCompilation: | no |
Language: | en-US |
Citation: | fmcmc citation info |
Materials: | NEWS ChangeLog |
CRAN checks: | fmcmc results |
Reference manual: | fmcmc.pdf |
Vignettes: |
User-defined kernels Workflow with fmcmc |
Package source: | fmcmc_0.2-0.tar.gz |
Windows binaries: | r-devel: fmcmc_0.2-0.zip, r-devel-gcc8: fmcmc_0.2-0.zip, r-release: fmcmc_0.2-0.zip, r-oldrel: fmcmc_0.2-0.zip |
OS X binaries: | r-release: fmcmc_0.2-0.tgz, r-oldrel: fmcmc_0.2-0.tgz |
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