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RcppHMM
View on CRAN: Click
here
Download and install RcppHMM package within the R console
Install from CRAN:
install.packages("RcppHMM")
Install from Github:
library("remotes")
install_github("cran/RcppHMM")
Install by package version:
library("remotes")
install_version("RcppHMM", "1.2.2")
Attach the package and use:
library("RcppHMM")
Maintained by
Roberto A. Cardenas-Ovando
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-02-08
Latest Update: 2017-11-21
Description:
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.
How to cite:
Roberto A. Cardenas-Ovando (2017). RcppHMM: Rcpp Hidden Markov Model. R package version 1.2.2, https://cran.r-project.org/web/packages/RcppHMM
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Other R packages that RcppHMM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the RcppHMM R package
Some associated functions: Changes . RcppHMM-package . evaluation . forwardBackward . generateObservations . initGHMM . initHMM . initPHMM . learnEM . loglikelihood . setNames . setParameters . verifyModel . viterbi .
Some associated R codes: RcppExports.R . Full RcppHMM package functions and examples
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