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 |
| 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 Mavericks binaries: | r-release: bayesMCClust_1.0.tgz, r-oldrel: bayesMCClust_1.0.tgz |
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