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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.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:

Please use the canonical form https://CRAN.R-project.org/package=RcppHMM to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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