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.
|Author||Christoph Pamminger <[email protected]>|
|Maintainer||Christoph Pamminger <[email protected]>|
|Package repository||View on CRAN|
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