Fit Hidden Markov Models using Template Model Builder
Overview
Fitting hidden Markov models using automatic differentiation and Laplace approximation, allowing for fast inference and flexible covariate effects (including random effects and smoothing splines) on model parameters. The package is described by Michelot (2025) doi:10.18637/jss.v114.i05.
- Add hurdle negative binomial distribution
- Fix bug in
HMM$fit_stan() - Fix bug in
HMM$pseudores()
From NEWS.md in the release
Install
Health
ERRORwhether package can be installedr-release-macos-x86_64
Installation failed. See ‘/Volumes/Builds/packages/big-sur-x86_64/results/4.6/hmmTMB.Rcheck/00install.out’ for details.
- ERROR12 OK, 1 ERRORNow
- ERROR11 OK, 1 ERROR2026-04-25
- NOTE11 OK, 3 NOTE2026-03-10
Documentation
- Help pages
- 32 (1 internal)includes a package overview page
- Examples that run
- 100%5 run in a plain check
- Exported functions with examples
- 27%
- Documented parameters
- 100%
- Return-value docs
- 33%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- 82%
- Median days to close, 50 most recently updated closed issues
- 4
- Median days to close, 50 most recently updated closed PRs
- 1
Forks over time
Issues over time
PRs over time
Commits over time
Commit identities over time
Checks run against github.com/theomichelot/hmmtmb on 2026-10-21.
No development-tooling practices detected in the upstream repository.
Dependencies
Code & Tests
People & History
Package metadata
- First published
- 2023-01-11
- Total releases
- 6 / 3 yrs
- License
- GPL-3 OSI
- Download size
- 230 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("hmmTMB")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.18637/jss.v114.i05.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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.