FourWayHMM: Parsimonious Hidden Markov Models for Four-Way Data

Implements parsimonious hidden Markov models for four-way data via expectation- conditional maximization algorithm, as described in Tomarchio et al. (2020) <arXiv:2107.04330>. The matrix-variate normal distribution is used as emission distribution. For each hidden state, parsimony is reached via the eigen-decomposition of the covariance matrices of the emission distribution. This produces a family of 98 parsimonious hidden Markov models.

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Package details

AuthorSalvatore D. Tomarchio [aut, cre], Antonio Punzo [aut], Antonello Maruotti [aut]
MaintainerSalvatore D. Tomarchio <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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FourWayHMM documentation built on Dec. 1, 2021, 1:06 a.m.