This directory contains a preliminary version of GRIMS, released 2011-08-26.

  The contents of this directory are Copyright (c) 2011 by Radford M. Neal.
  
  Permission is granted for anyone to copy, use, modify, or distribute these
  programs and accompanying documents for any purpose, provided this copyright
  notice is retained and prominently displayed, along with a note saying 
  that the original programs are available from Radford Neal's web page, and 
  note is made of any changes made to these programs.  These programs and 
  documents are distributed without any warranty, express or implied.  As the
  programs were written for research purposes only, they have not been tested 
  to the degree that would be advisable in any important application.  All use
  of these programs is entirely at the user's own risk.

This software can be obtained from http://www.cs.utoronto.ca/~radford/GRIMS.html

Release history:

  2011-08-26:  Fixed a bug in which mcmc returned a modified 'updates'
               list that then wouldn't work with more_mcmc.
  2011-08-10:  Varous mods and bug fixes (including for one bug with 
               rep>1 in metropolis, two bugs with lower and upper bound 
               attributes of lpr functions).
  2011-06-28:  Fixes bugs, adds Gibbs for normals, adds mvn tests.
  2011-06-25:  First release

---------------------------------------------------------------------

GRIMS - General R Interface for Markov Sampling - is an R package for
performing MCMC simulations, for distributions that are defined using
R functions, using Markov sampling methods that are defined by R
functions.

This preliminary version is not yet structured as a proper R package,
and has only two example distributions and three example sampling
methods.  It may also have lots of bugs.  It is being released mainly
for discussion.

Documentation for GRIMS is in several .txt files.  The starting point
is overview.txt.

Functions for defining multivariate normal distributions are in mvn.r

Functions defining a Bayesian logistic regression model are in
logistic.r.  These omit some facilities that would be present in a
final implementation of a logistic regression model.  (Some of these
omissions are deliberate, to allow testing that the framework handles
functions defining distribution which don't implement all features.)

Random-walk Metropolis updates with normal proposals are implemented
in metropolis.r.

A basic Hamiltonian Monte Carlo update is implemented in basic_hmc.r
and pupdate.r.

A Gibbs sampling procedure (currently for normal distributions only)
is in gibbs.r.

See the comments at the start of metropolis.r, basic_hmc.r, pupdate.r,
gibbs.r, mvn.r, and logistic.r for documentation on these examples.
Test runs of the sampling methods with the two distributions are in
mvn-tests.r and logistic-tests.r, both of which may be "sourced" to
run the tests (assuming that the other .r files are in the current
directory).