FourWayHMM: Parsimonious Hidden Markov Models for Four-Way Data
Salvatore D. Tomarchio, Antonio Punzo, Antonello Maruotti · 2021
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.