momentuHMM: Maximum Likelihood Analysis of Animal Movement Behavior Using Multivariate Hidden Markov Models

Extended tools for analyzing telemetry data using generalized hidden Markov models. These include data pre-processing and visualization, fitting HMMs to location and auxiliary biotelemetry or environmental data, biased and correlated random walk movement models, multiple imputation for incorporating location measurement error and missing data, user-specified design matrices and constraints for covariate modelling of parameters, 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>.

Version: 1.4.2
Depends: R (≥ 2.10)
Imports: Rcpp, doParallel, foreach, numDeriv, CircStats, crawl, ggmap, ggplot2, mitools, moveHMM, raster, argosfilter, car, mvtnorm, boot, sp, MASS, Brobdingnag, gstat, conicfit, nleqslv, survival, qdapRegex, geosphere, LaplacesDemon, prodlim, dplyr, magrittr
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, setRNG, knitr, splines, splines2 (≥ 0.2.8)
Published: 2018-06-20
Author: Brett McClintock, Theo Michelot
Maintainer: Brett McClintock <brett.mcclintock at>
License: GPL-3
NeedsCompilation: yes
Citation: momentuHMM citation info
Materials: README NEWS
CRAN checks: momentuHMM results


Reference manual: momentuHMM.pdf
Vignettes: Guide to using momentuHMM
Package source: momentuHMM_1.4.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: momentuHMM_1.4.2.tgz, r-oldrel: momentuHMM_1.4.2.tgz
Old sources: momentuHMM archive


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