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) doi:10.48550/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.
- Version1.0.0
- R version≥ 2.10
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release11/30/2021
Team
Salvatore D. Tomarchio
Antonio Punzo
Show author detailsRolesAuthorAntonello Maruotti
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- Imports9 packages