CRAN/E | FourWayHMM

FourWayHMM

Parsimonious Hidden Markov Models for Four-Way Data

Installation

About

Implements parsimonious hidden Markov models for four-way data via expectation- conditional maximization algorithm, as described in Tomarchio et al. (2020) . 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.

Key Metrics

Version 1.0.0
R ≥ 2.10
Published 2021-11-30 878 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks FourWayHMM results

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Maintainer

Maintainer

Salvatore D. Tomarchio

daniele.tomarchio@unict.it

Authors

Salvatore D. Tomarchio

aut / cre

Antonio Punzo

aut

Antonello Maruotti

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 2.10

Imports

withr
snow
doSNOW
foreach
mclust
tensor
tidyr
data.table
LaplacesDemon