Package: gibbs.met
Version: 1.1-3
Title: Naive Gibbs Sampling with Metropolis Steps
Author: Longhai Li <longhai@math.usask.ca>
Maintainer: Longhai Li <longhai@math.usask.ca>
Depends: R (>= 2.5.1)
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.
License: GPL (>= 2)
URL: \url{http://www.r-project.org},
        \url{http://math.usask.ca/~longhai}
Packaged: 2012-10-29 08:58:54 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:58:54
Built: R 3.1.0; ; 2013-10-24 14:46:41 UTC; unix
