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mcmc (version 0.9-8)

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

14,124

Version

0.9-8

License

MIT + file LICENSE

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Last Published

November 16th, 2023

Functions in mcmc (0.9-8)

olbm

Overlapping Batch Means
initseq

Initial Sequence Estimators
foo

Simulated logistic regression data.
temper

Simulated Tempering and Umbrella Sampling
logit

Simulated logistic regression data.
morph

Variable Transformation
morph.metrop

Morphometric Metropolis Algorithm
metrop

Metropolis Algorithm