MatrixHMM
Parsimonious Families of Hidden Markov Models for Matrix-Variate Longitudinal Data
Implements three families of parsimonious hidden Markov models (HMMs) for matrix-variate longitudinal data using the Expectation-Conditional Maximization (ECM) algorithm. The package supports matrix-variate normal, t, and contaminated normal distributions as emission distributions. For each hidden state, parsimony is achieved through the eigen-decomposition of the covariance matrices associated with the emission distribution. This approach results in a comprehensive set of 98 parsimonious HMMs for each type of emission distribution. Atypical matrix detection is also supported, utilizing the fitted (heavy-tailed) models.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | MatrixHMM_1.0.0.tar.gz |
123.5 KiB |
1.0.0 |
rolling linux/noble R-4.5 | MatrixHMM_1.0.0.tar.gz |
123.2 KiB |
1.0.0 |
rolling source/ R- | MatrixHMM_1.0.0.tar.gz |
32.8 KiB |
1.0.0 |
latest linux/jammy R-4.5 | MatrixHMM_1.0.0.tar.gz |
123.5 KiB |
1.0.0 |
latest linux/noble R-4.5 | MatrixHMM_1.0.0.tar.gz |
123.2 KiB |
1.0.0 |
latest source/ R- | MatrixHMM_1.0.0.tar.gz |
32.8 KiB |
1.0.0 |
2026-04-26 source/ R- | MatrixHMM_1.0.0.tar.gz |
32.8 KiB |
1.0.0 |
2026-04-23 source/ R- | MatrixHMM_1.0.0.tar.gz |
32.8 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | MatrixHMM_1.0.0.zip |
126.7 KiB |
1.0.0 |
2025-04-20 source/ R- | MatrixHMM_1.0.0.tar.gz |
32.8 KiB |