Package: RcppHMM 1.2.2

Roberto A. Cardenas-Ovando

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.

Authors:Roberto A. Cardenas-Ovando, Julieta Noguez and Claudia Rangel-Escareno

RcppHMM_1.2.2.tar.gz
RcppHMM_1.2.2.tar.gz(r-4.5-noble)RcppHMM_1.2.2.tar.gz(r-4.4-noble)
RcppHMM_1.2.2.tgz(r-4.4-emscripten)RcppHMM_1.2.2.tgz(r-4.3-emscripten)
RcppHMM.pdf |RcppHMM.html✨
RcppHMM/json (API)
NEWS

# Install 'RcppHMM' in R:
install.packages('RcppHMM', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 1 stars 177 downloads 12 exports 2 dependencies

Last updated 7 years agofrom:58fba0615f. Checks:1 OK, 2 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 20 2025
R-4.5-linux-x86_64NOTEMar 20 2025
R-4.4-linux-x86_64NOTEMar 20 2025

Exports:evaluationforwardBackwardgenerateObservationsinitGHMMinitHMMinitPHMMlearnEMloglikelihoodsetNamessetParametersverifyModelviterbi

Dependencies:RcppRcppArmadillo

Citation

To cite package ‘RcppHMM’ in publications use:

Cardenas-Ovando RA, Noguez J, Rangel-Escareno C (2017). RcppHMM: Rcpp Hidden Markov Model. R package version 1.2.2, https://CRAN.R-project.org/package=RcppHMM.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {RcppHMM: Rcpp Hidden Markov Model},
    author = {Roberto A. Cardenas-Ovando and Julieta Noguez and Claudia
      Rangel-Escareno},
    year = {2017},
    note = {R package version 1.2.2},
    url = {https://CRAN.R-project.org/package=RcppHMM},
  }