Package: plotHMM 2023.8.28
plotHMM: Plot Hidden Markov Models
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).
Authors:
plotHMM_2023.8.28.tar.gz
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plotHMM_2023.8.28.tgz(r-4.4-x86_64)plotHMM_2023.8.28.tgz(r-4.4-arm64)plotHMM_2023.8.28.tgz(r-4.3-x86_64)plotHMM_2023.8.28.tgz(r-4.3-arm64)
plotHMM_2023.8.28.tar.gz(r-4.5-noble)plotHMM_2023.8.28.tar.gz(r-4.4-noble)
plotHMM_2023.8.28.tgz(r-4.4-emscripten)plotHMM_2023.8.28.tgz(r-4.3-emscripten)
plotHMM.pdf |plotHMM.html✨
plotHMM/json (API)
NEWS
# Install 'plotHMM' in R: |
install.packages('plotHMM', repos = c('https://tdhock.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tdhock/plothmm/issues
- buggy.5states - Buggy data with 5 states
- buggy.data - Buggy data with one state
Last updated 1 years agofrom:e235971997. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-win-x86_64 | OK | Nov 06 2024 |
R-4.5-linux-x86_64 | OK | Nov 06 2024 |
R-4.4-win-x86_64 | OK | Nov 06 2024 |
R-4.4-mac-x86_64 | OK | Nov 06 2024 |
R-4.4-mac-aarch64 | OK | Nov 06 2024 |
R-4.3-win-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-aarch64 | OK | Nov 06 2024 |
Exports:backward_interfaceelnproductelnsumforward_interfacelogsumexpmultiply_interfacepairwise_interfacetransition_interfaceviterbi_interface
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Backward algorithm | backward_interface |
Buggy data with 5 states | buggy.5states |
Buggy data with one state | buggy.data |
Log probability arithmetic | elnproduct elnsum logsumexp |
Forward algorithm | forward_interface |
Multiply algorithm | multiply_interface |
Pairwise algorithm | pairwise_interface |
Transition algorithm | transition_interface |
Viterbi algorithm | viterbi_interface |