gibbs.met: Naive Gibbs Sampling with Metropolis Steps
Version 1.1-3

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.

Getting started

Package details

AuthorLonghai Li <[email protected]>
Date of publication2012-10-29 08:58:54
MaintainerLonghai Li <[email protected]>
LicenseGPL (>= 2)
Version1.1-3
URL \url{http://www.r-project.org} \url{http://math.usask.ca/~longhai}
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("gibbs.met")

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gibbs.met documentation built on May 30, 2017, 4:58 a.m.