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mcmc (version 0.9-4)

Markov Chain Monte Carlo

Description

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, Annals of Statistics, 2012, function morph.metrop), which achieves geometric ergodicity by change of variable.

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Install

install.packages('mcmc')

Monthly Downloads

12,172

Version

0.9-4

License

MIT + file LICENSE

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Maintainer

Charles Geyer

Last Published

July 16th, 2015

Functions in mcmc (0.9-4)

morph.metrop

Morphometric Metropolis Algorithm
initseq

Initial Sequence Estimators
metrop

Metropolis Algorithm
logit

Simulated logistic regression data.
foo

Simulated logistic regression data.
morph

Variable Transformation
temper

Simulated Tempering and Umbrella Sampling
olbm

Overlapping Batch Means