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: | 2022.1.25 |
| Imports: | Rcpp (≥ 1.0.7) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat, knitr, markdown, R.utils, covr, depmixS4, data.table, ggplot2, neuroblastoma, microbenchmark |
| Published: | 2022-01-27 |
| 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.pdf |
| Vignettes: |
Comparison with depmixS4 Multiple sequences |
| Package source: | plotHMM_2022.1.25.tar.gz |
| Windows binaries: | r-devel: plotHMM_2022.1.25.zip, r-release: plotHMM_2022.1.25.zip, r-oldrel: plotHMM_2022.1.25.zip |
| macOS binaries: | r-release (arm64): plotHMM_2022.1.25.tgz, r-oldrel (arm64): plotHMM_2022.1.25.tgz, r-release (x86_64): plotHMM_2022.1.25.tgz, r-oldrel (x86_64): plotHMM_2022.1.25.tgz |
| Old sources: | plotHMM archive |
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