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:Toby Hocking [aut, cre]

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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'))

Peer review:

Bug tracker:https://github.com/tdhock/plothmm/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

3.30 score 3 scripts 260 downloads 9 exports 2 dependencies

Last updated 1 years agofrom:e235971997. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64OKNov 06 2024
R-4.5-linux-x86_64OKNov 06 2024
R-4.4-win-x86_64OKNov 06 2024
R-4.4-mac-x86_64OKNov 06 2024
R-4.4-mac-aarch64OKNov 06 2024
R-4.3-win-x86_64OKNov 06 2024
R-4.3-mac-x86_64OKNov 06 2024
R-4.3-mac-aarch64OKNov 06 2024

Exports:backward_interfaceelnproductelnsumforward_interfacelogsumexpmultiply_interfacepairwise_interfacetransition_interfaceviterbi_interface

Dependencies:RcppRcppArmadillo

Comparison with depmixS4

Rendered fromcompare_depmixS4.Rmdusingknitr::knitron Nov 06 2024.

Last update: 2023-08-29
Started: 2021-10-18

Multiple sequences

Rendered frommultiple_sequences.Rmdusingknitr::knitron Nov 06 2024.

Last update: 2021-10-27
Started: 2021-10-27

Readme and manuals

Help Manual

Help pageTopics
Backward algorithmbackward_interface
Buggy data with 5 statesbuggy.5states
Buggy data with one statebuggy.data
Log probability arithmeticelnproduct elnsum logsumexp
Forward algorithmforward_interface
Multiply algorithmmultiply_interface
Pairwise algorithmpairwise_interface
Transition algorithmtransition_interface
Viterbi algorithmviterbi_interface