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mcmc: Markov Chain Monte Carlo

Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, <doi:10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.

Version: 0.9-8
Depends: R (≥ 3.6.0)
Imports: stats
Suggests: xtable, Iso
Published: 2023-11-16
DOI: 10.32614/CRAN.package.mcmc
Author: Charles J. Geyer and Leif T. Johnson
Maintainer: Charles J. Geyer <geyer at umn.edu>
License: MIT + file LICENSE
URL: http://www.stat.umn.edu/geyer/mcmc/, https://github.com/cjgeyer/mcmc
NeedsCompilation: yes
Materials: ChangeLog
In views: Bayesian
CRAN checks: mcmc results

Documentation:

Reference manual: mcmc.pdf
Vignettes: Bayes Factors via Serial Tempering
Debugging MCMC Code
MCMC Example
MCMC Morph Example

Downloads:

Package source: mcmc_0.9-8.tar.gz
Windows binaries: r-devel: mcmc_0.9-8.zip, r-release: mcmc_0.9-8.zip, r-oldrel: mcmc_0.9-8.zip
macOS binaries: r-release (arm64): mcmc_0.9-8.tgz, r-oldrel (arm64): mcmc_0.9-8.tgz, r-release (x86_64): mcmc_0.9-8.tgz, r-oldrel (x86_64): mcmc_0.9-8.tgz
Old sources: mcmc archive

Reverse dependencies:

Reverse imports: geommc, MCMCpack, nse, prefeR, ReliabilityTheory
Reverse suggests: ConnMatTools, fmcmc, MSGARCH

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mcmc to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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