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FourWayHMM (version 1.0.0)

Parsimonious Hidden Markov Models for Four-Way Data

Description

Implements parsimonious hidden Markov models for four-way data via expectation- conditional maximization algorithm, as described in Tomarchio et al. (2020) . 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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Version

Install

install.packages('FourWayHMM')

Monthly Downloads

286

Version

1.0.0

License

GPL (>= 3)

Maintainer

Salvatore D. Tomarchio

Last Published

November 30th, 2021

Functions in FourWayHMM (1.0.0)

simX

Simulated Data
HMM.init

Initialization for the ECM algorithm
HMM.fit

Fitting for parsimonious hidden Markov models for four-way data