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mcmc (version 0.9-7)

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

15,125

Version

0.9-7

License

MIT + file LICENSE

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Maintainer

Charles Geyer

Last Published

March 21st, 2020

Functions in mcmc (0.9-7)

temper

Simulated Tempering and Umbrella Sampling
logit

Simulated logistic regression data.
olbm

Overlapping Batch Means
metrop

Metropolis Algorithm
morph

Variable Transformation
initseq

Initial Sequence Estimators
foo

Simulated logistic regression data.
morph.metrop

Morphometric Metropolis Algorithm