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MHadaptive (version 1.1-8)

General Markov Chain Monte Carlo for Bayesian Inference using adaptive Metropolis-Hastings sampling

Description

Performs general Metropolis-Hastings Markov Chain Monte Carlo sampling of a user defined function which returns the un-normalized value (likelihood times prior) of a Bayesian model. The proposal variance-covariance structure is updated adaptively for efficient mixing when the structure of the target distribution is unknown. The package also provides some functions for Bayesian inference including Bayesian Credible Intervals (BCI) and Deviance Information Criterion (DIC) calculation.

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Version

Install

install.packages('MHadaptive')

Monthly Downloads

62

Version

1.1-8

License

GPL (>= 3)

Maintainer

Corey Chivers

Last Published

March 24th, 2012

Functions in MHadaptive (1.1-8)

BCI

Bayesian Credible Interval
plotMH

Plot MCMC results of a call to Metro_Hastings().
MHadaptive-package

General Markov Chain Monte Carlo for Bayesian Inference using adaptive Metropolis-Hastings sampling
mcmc_r

A sample object created by running Metro_Hastings().
mcmc_thin

Thin an MCMC object to reduce autocorrelation.
Metro_Hastings

Markov Chain Monte Carlo for Bayesian Inference using adaptive Metropolis-Hastings
positiveDefinite

Positive Definite Matrixes