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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 |
| 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 |
| Reference manual: | RcppHMM.pdf |
| 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 suggests: | nullranges |
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