Plot Hidden Markov Models
Overview
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).
- Convert NEWS.
- Use Suggests conditionally.
From NEWS in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 9
- Examples that run
- 100%7 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 11%
Downloads
Dependencies
Installing plotHMM adds 2 packages (2 with compiled code, 2.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 2023.8.28Latest
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 2022.1.252022-01-27 · diff ↗
- 2022.1.182022-01-19
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-01-19
- Total releases
- 3 / 4 yrs
- License
- GPL (>= 2) OSI
- Bundled data
- 40 KB / 2 files
- Download size
- 191 KB
Cite
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Run in R for the authors' preferred citation:
citation("plotHMM")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
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From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.