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, 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>.

Version: 1.5.5
Depends: R (≥ 2.10)
Imports: Rcpp, doParallel, foreach, numDeriv, CircStats, crawl (≥ 2.2.1), mvtnorm, sp, MASS, Brobdingnag, doRNG, rlang, raster
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, setRNG, splines, splines2 (≥ 0.2.8), R.rsp, conicfit, ggplot2, ggmap, lubridate, dplyr, magrittr, scatterplot3d, BB, expm, matrixcalc, moveHMM, extraDistr, data.tree (≥ 1.0.0), geosphere, mitools, doFuture, future, car, survival, prodlim, nleqslv, qdapRegex
Published: 2022-10-18
DOI: 10.32614/CRAN.package.momentuHMM
Author: Brett McClintock, Theo Michelot
Maintainer: Brett McClintock <brett.mcclintock at>
License: GPL-3
NeedsCompilation: yes
Citation: momentuHMM citation info
Materials: README NEWS
In views: MissingData, SpatioTemporal, Tracking
CRAN checks: momentuHMM results


Reference manual: momentuHMM.pdf
Vignettes: Guide to using momentuHMM


Package source: momentuHMM_1.5.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): momentuHMM_1.5.5.tgz, r-oldrel (arm64): momentuHMM_1.5.5.tgz, r-release (x86_64): momentuHMM_1.5.5.tgz, r-oldrel (x86_64): momentuHMM_1.5.5.tgz
Old sources: momentuHMM archive


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