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 |
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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 |
Documentation:
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