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MatrixHMM

1.0.0Package record

Parsimonious Families of Hidden Markov Models for Matrix-Variate Longitudinal Data

0packages depend
2.6Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Install

Health

CRAN checks
13OK
Slowest check: 1.6 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-10-20
  • ERROR12 OK, 1 ERROR2026-10-17
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
Show 7 earlier changesHide 7 earlier changes
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-07-04
  • ERROR12 OK, 1 ERROR2026-07-03
  • OK14 OK2026-03-31
  • ERROR13 OK, 1 ERROR2026-03-30
  • OK14 OK2026-03-21
  • ERROR13 OK, 1 ERROR2026-03-10
Advisories

none known

Documentation

In release 1.0.0
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
8
Examples that run
100%6 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

2.6K
CRAN downloads in the past year
Rank #22,613 · ~7/day · ~213/mo
Daily download trend is not available in this view yet.
20330 days
58890 days
2.6K1 year
Compare downloads with other packages →
Also on68 r2u3 autocran

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)

Installing MatrixHMM adds 32 packages (14 with compiled code, 29 MB of source tarballs). Heaviest: stringi 11 MB, data.table 5.7 MB, mclust 2.7 MB.

Depends (1)
R >= 2.10
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (1)
Author, Maintainer since 1.0.0 (2024)
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.0.0Latest
    2024-08-28 · current release
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-08-28
Total releases
1 / 2 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 2.10
Bundled data
15 KB / 2 files
Download size
32 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MatrixHMM")
Tomarchio, S. D. (2024). MatrixHMM: Parsimonious Families of Hidden Markov Models for Matrix-Variate Longitudinal Data (Version 1.0.0) [Computer software]. https://doi.org/10.32614/CRAN.package.MatrixHMM

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for MatrixHMM version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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