Package: RcppHMM 1.2.2.1
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:
RcppHMM_1.2.2.1.tar.gz
RcppHMM_1.2.2.1.zip(r-4.7-x86_64)RcppHMM_1.2.2.1.zip(r-4.7-arm64)RcppHMM_1.2.2.1.zip(r-4.6-x86_64)RcppHMM_1.2.2.1.zip(r-4.6-arm64)
RcppHMM_1.2.2.1.tar.gz(r-4.7-arm64)RcppHMM_1.2.2.1.tar.gz(r-4.7-x86_64)RcppHMM_1.2.2.1.tar.gz(r-4.6-arm64)RcppHMM_1.2.2.1.tar.gz(r-4.6-x86_64)
RcppHMM_1.2.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RcppHMM/json (API)
| # Install 'RcppHMM' in R: |
| install.packages('RcppHMM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:92bd8e39de. Checks:10 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 124 | ||
| linux-devel-x86_64 | OK | 140 | ||
| source / vignettes | OK | 239 | ||
| linux-release-arm64 | OK | 118 | ||
| linux-release-x86_64 | OK | 119 | ||
| windows-devel-arm64 | OK | 217 | ||
| windows-devel-x86_64 | OK | 166 | ||
| windows-release-arm64 | OK | 245 | ||
| windows-release-x86_64 | OK | 136 | ||
| wasm-release | OK | 135 |
Exports:evaluationforwardBackwardgenerateObservationsinitGHMMinitHMMinitPHMMlearnEMloglikelihoodsetNamessetParametersverifyModelviterbi
Dependencies:RcppRcppArmadillo
