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>.
| Version: |
2.0.0 |
| Depends: |
R6, mgcv, TMB, ggplot2 |
| Imports: |
Matrix, stringr, MASS, tmbstan, methods, fmesher |
| LinkingTo: |
TMB, RcppEigen |
| Suggests: |
rstan, testthat, knitr, rmarkdown, expm, MSwM |
| Published: |
2026-11-10 |
| DOI: |
10.32614/CRAN.package.hmmTMB |
| Author: |
Theo Michelot [aut, cre],
Richard Glennie [aut],
Jan-Ole Fischer [ctb] (SPDE smooths),
Duncan Cameron-Steinke [ctb] (Forecast class),
Pauline Rocu [ctb] (schisq distribution),
Litty Mathew [ctb] (hnbinom distribution) |
| Maintainer: |
Theo Michelot <theo.michelot at dal.ca> |
| License: |
GPL-3 |
| URL: |
https://github.com/TheoMichelot/hmmTMB |
| NeedsCompilation: |
yes |
| Citation: |
hmmTMB citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
hmmTMB results |