depmixS4: Dependent Mixture Models - Hidden Markov Models of GLMs and Other Distributions in S4

Fits latent (hidden) Markov models on mixed categorical and continuous (time series) data, otherwise known as dependent mixture models, see Visser & Speekenbrink (2010, <doi:10.18637/jss.v036.i07>).

Version:	1.5-0
Depends:	R (≥ 4.0.0), nnet, MASS, Rsolnp, nlme
Imports:	stats, stats4, methods
Suggests:	gamlss, gamlss.dist, Rdonlp2
Published:	2021-05-12
Author:	Ingmar Visser, Maarten Speekenbrink
Maintainer:	Ingmar Visser <i.visser at uva.nl>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://depmix.github.io/
NeedsCompilation:	yes
Additional_repositories:	http://R-Forge.R-project.org
Citation:	depmixS4 citation info
Materials:	README NEWS
In views:	Cluster, TimeSeries
CRAN checks:	depmixS4 results

Documentation:

Reference manual:	depmixS4.pdf
Vignettes:	depmixS4: An R Package for Hidden Markov Models

Downloads:

Package source:	depmixS4_1.5-0.tar.gz
Windows binaries:	r-devel: depmixS4_1.5-0.zip, r-release: depmixS4_1.5-0.zip, r-oldrel: depmixS4_1.5-0.zip
macOS binaries:	r-release (arm64): depmixS4_1.5-0.tgz, r-oldrel (arm64): depmixS4_1.5-0.tgz, r-release (x86_64): depmixS4_1.5-0.tgz, r-oldrel (x86_64): depmixS4_1.5-0.tgz
Old sources:	depmixS4 archive

Reverse dependencies:

Reverse depends:	hmmr
Reverse imports:	InPAS
Reverse suggests:	ldhmm, plotHMM, segclust2d

Linking:

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