MCMCpack: Markov chain Monte Carlo (MCMC) Package

This package contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return coda mcmc objects that can then be summarized using the coda package. MCMCpack also contains some useful utility functions, including some additional density functions and pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization.

Version: 1.3-3
Depends: R (≥ 2.10.0), coda (≥ 0.11-3), MASS, stats
Published: 2013-05-01
Author: Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park
Maintainer: Jong Hee Park <jongheepark at snu.ac.kr>
License: GPL-3
URL: http://mcmcpack.wustl.edu
NeedsCompilation: yes
SystemRequirements: gcc (>= 4.0)
Citation: MCMCpack citation info
Materials: README
In views: Bayesian, Distributions, Multivariate, Psychometrics, Survival
CRAN checks: MCMCpack results

Downloads:

Reference manual: MCMCpack.pdf
Package source: MCMCpack_1.3-3.tar.gz
MacOS X binary: MCMCpack_1.3-3.tgz
Windows binary: MCMCpack_1.3-3.zip
Old sources: MCMCpack archive

Reverse dependencies:

Reverse depends: adaptsmoFMRI, anominate, BayesCR, BayesMed, bayespref, CoinMinD, cudia, hierarchicalDS, HMP, HSROC, hzar, miscF, PhViD, R2GUESS, RxCEcolInf, SimpleTable, StVAR
Reverse imports: BayesLCA, BayesSingleSub, coarseDataTools, HWEBayes, spikeSlabGAM
Reverse suggests: BayesDA, DOBAD, dyn, frontier, harvestr, IPMpack, pscl, SciencesPo, Zelig