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mcmc (version 0.9-6)

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

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Install

install.packages('mcmc')

Monthly Downloads

21,698

Version

0.9-6

License

MIT + file LICENSE

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Maintainer

Charles Geyer

Last Published

March 10th, 2019

Functions in mcmc (0.9-6)

foo

Simulated logistic regression data.
olbm

Overlapping Batch Means
initseq

Initial Sequence Estimators
logit

Simulated logistic regression data.
temper

Simulated Tempering and Umbrella Sampling
metrop

Metropolis Algorithm
morph

Variable Transformation
morph.metrop

Morphometric Metropolis Algorithm