RcppHMM: Rcpp Hidden Markov Model

Collection of functions to evaluate sequences, decode hidden states and estimate parameters from a single or multiple sequences of a discrete time Hidden Markov Model. The observed values can be modeled by a multinomial distribution for categorical/labeled emissions, a mixture of Gaussians for continuous data and also a mixture of Poissons for discrete values. It includes functions for random initialization, simulation, backward or forward sequence evaluation, Viterbi or forward-backward decoding and parameter estimation using an Expectation-Maximization approach.

Version:	1.2.2
Imports:	Rcpp (≥ 0.12.6)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2017-11-21
DOI:	10.32614/CRAN.package.RcppHMM
Author:	Roberto A. Cardenas-Ovando, Julieta Noguez and Claudia Rangel-Escareno
Maintainer:	Roberto A. Cardenas-Ovando <robalecarova at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
SystemRequirements:	C++11
Materials:	NEWS
CRAN checks:	RcppHMM results

Documentation:

Reference manual:

RcppHMM.html , RcppHMM.pdf

Downloads:

Package source:	RcppHMM_1.2.2.tar.gz
Windows binaries:	r-devel: RcppHMM_1.2.2.zip, r-release: RcppHMM_1.2.2.zip, r-oldrel: RcppHMM_1.2.2.zip
macOS binaries:	r-release (arm64): RcppHMM_1.2.2.tgz, r-oldrel (arm64): RcppHMM_1.2.2.tgz, r-release (x86_64): RcppHMM_1.2.2.tgz, r-oldrel (x86_64): RcppHMM_1.2.2.tgz
Old sources:	RcppHMM archive

Reverse dependencies:

Reverse suggests:

nullranges

Linking:

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