Package: fmcmc Title: A friendly MCMC framework Version: 0.6-0 Date: 2025-12-03 Authors@R: c(person("George", "Vega Yon", email = "g.vegayon@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3171-0844")), person("Paul", "Marjoram", email = "pmarjora@usc.edu", role = c("ctb", "ths"), comment = c(ORCID = "0000-0003-0824-7449")), person("National Cancer Institute (NCI)", role = "fnd", comment = "Grant Number 5P01CA196569-02"), person("Fabian", "Scheipl", role = "rev", comment = c(what = "JOSS reviewer", ORCID="0000-0001-8172-3603")) ) Description: 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. Depends: R (>= 3.3.0) License: MIT + file LICENSE Encoding: UTF-8 Language: en-US LazyData: true URL: https://github.com/USCbiostats/fmcmc, https://uscbiostats.github.io/fmcmc/ BugReports: https://github.com/USCbiostats/fmcmc/issues Suggests: covr, knitr, rmarkdown, mcmc, tinytest, mvtnorm, Imports: parallel, coda, stats, methods, MASS, Matrix RoxygenNote: 7.3.3 Roxygen: list(markdown = TRUE) VignetteBuilder: knitr Repository: https://uscbiostats.r-universe.dev Date/Publication: 2025-12-12 15:50:38 UTC RemoteUrl: https://github.com/uscbiostats/fmcmc RemoteRef: HEAD RemoteSha: d7330a7d899b210f912f2e5313b11587bc108675 NeedsCompilation: no Packaged: 2026-06-10 08:29:58 UTC; root Author: George Vega Yon [aut, cre] (ORCID: ), Paul Marjoram [ctb, ths] (ORCID: ), National Cancer Institute (NCI) [fnd] (Grant Number 5P01CA196569-02), Fabian Scheipl [rev] (what: JOSS reviewer, ORCID: ) Maintainer: George Vega Yon