momentuHMM - Maximum Likelihood Analysis of Animal Movement Behavior Using
Multivariate Hidden Markov Models
Extended tools for analyzing telemetry data using
generalized hidden Markov models. Features of momentuHMM
(pronounced ``momentum'') include data pre-processing and
visualization, fitting HMMs to location and auxiliary
biotelemetry or environmental data, biased and correlated
random walk movement models, discrete- or continuous-time HMMs,
continuous- or discrete-space movement models, approximate
Langevin diffusion models, hierarchical HMMs, multiple
imputation for incorporating location measurement error and
missing data, user-specified design matrices and constraints
for covariate modelling of parameters, random effects, decoding
of the state process, visualization of fitted models, model
checking and selection, and simulation. See McClintock and
Michelot (2018) <doi:10.1111/2041-210X.12995>.
