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.
|Depends:||R (≥ 2.14.1), gplots, xtable, grDevices, mnormt, MASS, bayesm, boa, e1071, gtools|
|Maintainer:||Christoph Pamminger <christoph.pamminger at gmail.com>|
|CRAN checks:||bayesMCClust results|
|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-release: bayesMCClust_1.0.tgz, r-oldrel: bayesMCClust_1.0.tgz|
|OS X Mavericks binaries:||r-release: bayesMCClust_1.0.tgz|