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 (2022) arXiv:2211.14139.
Maintainer: Theo Michelot theo.michelot@dal.ca
Authors:
Richard Glennie [contributor]
The package hmmTMB is based on three main classes (i.e., types of objects): MarkovChain, Observation, and HMM. Type ?MarkovChain, ?Observation or ?HMM to find their documentation, or consult the package vignettes for detailed examples of the hmmTMB workflow.
Useful links: