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.

Package details

AuthorRoberto A. Cardenas-Ovando, Julieta Noguez and Claudia Rangel-Escareno
MaintainerRoberto A. Cardenas-Ovando <robalecarova@gmail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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RcppHMM documentation built on May 2, 2019, 8:56 a.m.