fmcmc: 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).

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 ORCID iD [aut, cre], Paul Marjoram ORCID iD [ctb, ths], National Cancer Institute (NCI) [fnd] (Grant Number 5P01CA196569-02), Fabian Scheipl ORCID iD [rev] (JOSS reviewer)
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

Downloads:

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-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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