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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling source/ R- | FourWayHMM_1.0.0.tar.gz |
32.5 KiB |
1.0.0 |
latest source/ R- | FourWayHMM_1.0.0.tar.gz |
32.5 KiB |
1.0.0 |
2026-04-23 source/ R- | FourWayHMM_1.0.0.tar.gz |
32.5 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | FourWayHMM_1.0.0.zip |
85.1 KiB |