DBHC 0.0.2

Sequence Clustering with Discrete-Output HMMs

Released Apr 13, 2018 by Gabriel Budel

This package cannot yet be used with Renjin it depends on other packages which are not available: seqHMM 1.0.8-1


seqHMM 1.0.8-1 ggplot2 3.0.0 TraMineR 2.0-9 reshape2 1.4.3

Provides an implementation of a mixture of hidden Markov models (HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering (DBHC) algorithm. The DBHC algorithm is an HMM Clustering algorithm that finds a mixture of discrete-output HMMs while using heuristics based on Bayesian Information Criterion (BIC) to search for the optimal number of HMM states and the optimal number of clusters.



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