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FourWayHMM

1.0.0Package record

Parsimonious Hidden Markov Models for Four-Way Data

0packages depend
3.2Kdownloads / year
–test coverage
9/13flavors OK

Overview

About

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.

Install

Health

CRAN checks
4NOTE9OK
Check messages
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Salvatore D. Tomarchio <daniele.tomarchio@unict.it>’

The Description field contains
  Tomarchio et al. (2020) <arXiv:2107.04330>.  The matrix-variate normal
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespace in Imports field not imported from:
  ‘LaplacesDemon’
All declared Imports should be used.

CRAN check page ↗

Slowest check: 56 s · r-oldrel-windows-x86_64
Status changes
  • NOTE9 OK, 4 NOTENow
  • NOTE10 OK, 4 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.0.0
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
3
Examples that run
100%2 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

3.2K
CRAN downloads in the past year
Rank #18,067 · ~9/day · ~267/mo
Daily download trend is not available in this view yet.
26730 days
71090 days
3.2K1 year
Compare downloads with other packages →
Also on69 r2u4 autocran

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)

Installing FourWayHMM adds 28 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 (3)
Author, Maintainer since 1.0.0 (2021)
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0.0Latest
    2021-11-30 · current release
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2021-11-30
Total releases
1 / 5 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 2.10
Bundled data
23 KB / 1 file
Download size
33 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("FourWayHMM")
Tomarchio, S. D., Maruotti, A., & Punzo, A. (2021). FourWayHMM: Parsimonious Hidden Markov Models for Four-Way Data (Version 1.0.0) [Computer software]. https://doi.org/10.32614/CRAN.package.FourWayHMM

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 FourWayHMM version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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