Package: FourWayHMM
Title: Parsimonious Hidden Markov Models for Four-Way Data
Version: 1.0.0
Authors@R: c(
    person(given = "Salvatore D.",
           family = "Tomarchio",
           role = c("aut","cre"),
           email = "daniele.tomarchio@unict.it"),
    person(given = "Antonio",
           family = "Punzo",
           role = "aut"),
    person(given = "Antonello",
           family = "Maruotti",
           role = "aut"))
Description: 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.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: withr, snow, doSNOW, foreach, mclust, tensor, tidyr,
        data.table, LaplacesDemon
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2026-07-13 07:00:13 UTC; root
Author: Salvatore D. Tomarchio [aut, cre], Antonio Punzo [aut],
        Antonello Maruotti [aut]
Maintainer: Salvatore D. Tomarchio <daniele.tomarchio@unict.it>
Repository: https://cran.r-universe.dev
Date/Publication: 2021-11-30 20:20:02 UTC
RemoteUrl: https://github.com/cran/FourWayHMM
RemoteRef: HEAD
RemoteSha: f180b5bbd9518704132d3f54f5f1836ab7c43768