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). Among the methods included, we have: Haario (2001) <doi:10.1007/s11222-011-9269-5> Adaptive Metropolis, Vihola (2012) <doi:10.1007/s11222-011-9269-5> Robust Adaptive Metropolis, and Thawornwattana et al. (2018) <doi:10.1214/17-BA1084> Mirror transition kernels.

Package details

AuthorGeorge Vega Yon [aut, cre] (<https://orcid.org/0000-0002-3171-0844>), Paul Marjoram [ctb, ths] (<https://orcid.org/0000-0003-0824-7449>), National Cancer Institute (NCI) [fnd] (Grant Number 5P01CA196569-02), Fabian Scheipl [rev] (JOSS reviewer, <https://orcid.org/0000-0001-8172-3603>)
MaintainerGeorge Vega Yon <g.vegayon@gmail.com>
LicenseMIT + file LICENSE
Version0.5-1
URL https://github.com/USCbiostats/fmcmc
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fmcmc")

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fmcmc documentation built on Jan. 14, 2022, 9:07 a.m.