RcppHMM: Rcpp Hidden Markov Model (original) (raw)

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
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
Materials:
CRAN checks: RcppHMM results

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