gibbs.met (version 1.1-3)
Naive Gibbs Sampling with Metropolis Steps
Description
This package provides two generic functions for performing
Markov chain sampling in a naive way for a user-defined target
distribution, which involves only continuous variables. The
function "gibbs_met" performs Gibbs sampling with each
1-dimensional distribution sampled with Metropolis update using
Gaussian proposal distribution centered at the previous state.
The function "met_gaussian" updates the whole state with
Metropolis method using independent Gaussian proposal
distribution centered at the previous state. The sampling is
carried out without considering any special tricks for
improving efficiency. This package is aimed at only routine
applications of MCMC in moderate-dimensional problems.