hmma: Constructs Asymmetric Hidden Markov Models

Asymmetric hidden Markov model (HMM-A) learning. HMM-As are similar to regular HMMs, but use Bayesian Networks (BNs) in their emission distribution. The HMM-As can therefore offer more problem insight [Bueno et al. 2017, <doi:10.1016/j.ijar.2017.05.011>].

Version: 1.0.0
Depends: R (≥ 3.6.0)
Imports: bnlearn, mhsmm, MCMCpack, Rgraphviz, graph, methods
Suggests: knitr, testthat, rmarkdown
Published: 2020-04-08
Author: Marcos L.P Bueno [aut], Arjen Hommersom [aut, cre], Joop Thibaudier [aut], Marco Scutari [ctb], Robert Ness [ctb], Robert Gentleman and Ross Ihaka [cph], The R Development Core Team [cph], The R Foundation [cph]
Maintainer: Arjen Hommersom <arjen.hommersom at ou.nl>
License: GPL-3
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: hmma results

Downloads:

Reference manual: hmma.pdf
Vignettes: Introduction to the hmma package
Package source: hmma_1.0.0.tar.gz
Windows binaries: r-devel: hmma_1.0.0.zip, r-release: hmma_1.0.0.zip, r-oldrel: hmma_1.0.0.zip
macOS binaries: r-release: hmma_1.0.0.tgz, r-oldrel: hmma_1.0.0.tgz

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