bayesMCClust: Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering

This package provides various Markov Chain Monte Carlo (MCMC) sampler for model-based clustering of discrete-valued time series obtained by observing a categorical variable with several states (in a Bayesian approach). In order to analyze group membership, we provide also an extension to the approaches by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule using a multinomial logit model.

Version: 1.0
Depends: R (≥ 2.14.1), gplots, xtable, grDevices, mnormt, MASS, bayesm, boa, e1071, gtools
Suggests: nnet
Published: 2012-01-31
Author: Christoph Pamminger
Maintainer: Christoph Pamminger <christoph.pamminger at gmail.com>
License: GPL-2
NeedsCompilation: no
In views: Cluster
CRAN checks: bayesMCClust results

Downloads:

Reference manual: bayesMCClust.pdf
Package source: bayesMCClust_1.0.tar.gz
Windows binaries: r-devel: bayesMCClust_1.0.zip, r-release: bayesMCClust_1.0.zip, r-oldrel: bayesMCClust_1.0.zip
OS X Snow Leopard binaries: r-oldrel: bayesMCClust_1.0.tgz
OS X Mavericks binaries: r-release: bayesMCClust_1.0.tgz