Hidden Markov Models are useful for modeling sequential data. This package provides several functions implemented in C++ for explaining the algorithms used for Hidden Markov Models (forward, backward, decoding, learning).
| Version: | 2023.8.28 |
| Imports: | Rcpp (≥ 1.0.7) |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | testthat,knitr,markdown,R.utils,covr,depmixS4,data.table,ggplot2,neuroblastoma,microbenchmark |
| Published: | 2023-09-05 |
| DOI: | 10.32614/CRAN.package.plotHMM |
| Author: | Toby Hocking [aut, cre] |
| Maintainer: | Toby Hocking <toby.hocking at r-project.org> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | plotHMM results |
| Reference manual: | plotHMM.html ,plotHMM.pdf |
| Vignettes: | Comparison with depmixS4 (source,R code) Multiple sequences (source,R code) |
| Package source: | plotHMM_2023.8.28.tar.gz |
| Windows binaries: | r-devel:plotHMM_2023.8.28.zip, r-release:plotHMM_2023.8.28.zip, r-oldrel:plotHMM_2023.8.28.zip |
| macOS binaries: | r-release (arm64):plotHMM_2023.8.28.tgz, r-oldrel (arm64):plotHMM_2023.8.28.tgz, r-release (x86_64):plotHMM_2023.8.28.tgz, r-oldrel (x86_64):plotHMM_2023.8.28.tgz |
| Old sources: | plotHMM archive |
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