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, , function morph.metrop), which achieves geometric ergodicity by change of variable.

Maintainer: Charles J. Geyer <charlie at stat.umn.edu>

Author(s): Charles J. Geyer <charlie at stat.umn.edu> and Leif T. Johnson <ltjohnson at google.com>

Install package and any missing dependencies by running this line in your R console:

install.packages("mcmc")

Depends R (>= 3.0.2)
Imports stats, compiler
Suggests xtable, Iso
Enhances
Linking to
Reverse
depends
ltbayes
Reverse
imports
MCMCpack, nse, prefeR, ReliabilityTheory, sizeMat, TBSSurvival
Reverse
suggests
ConnMatTools, pse
Reverse
enhances
Reverse
linking to

Package mcmc
Materials
URL http://www.stat.umn.edu/geyer/mcmc/ https://github.com/cjgeyer/mcmc
Task Views Bayesian
Version 0.9-5
Published 2017-04-16
License MIT + file LICENSE
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks mcmc check results
Package source mcmc_0.9-5.tar.gz