We developed the R package moveHMM for the analysis of movement data with hidden Markov models.
CRAN: description, documentation, archives…
Github: latest (unstable) version of the code.
Get started with the vignette. There, we describe the functionalities of the package in detail, and illustrate their use on elk tracking data.
Short video presentation for MEE.
The R package momentuHMM extends moveHMM to more general and flexible models. Additional features include: unlimited number of data streams, inclusion of covariates on the observation distribution parameters, centres of attraction, multiple imputation to account for irregular sampling and/or measurement error, etc.
Other R packages
Vianey Leos Barajas and I wrote a tutorial about using Stan to implement hidden Markov models, in particular to analyse animal movement data. In that document, we re-analyse the wild haggis data set from the moveHMM paper.
A while ago, I also wrote a document about implementing hidden Markov models in R and/or C++ (using Rcpp). It describes two examples in detail: a 2-state HMM with Poisson-distributed observations, and a 3-state HMM inspired by movement models. R code is provided for simulation, estimation, and inference in these models.