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momentuHMM

R package for Maximum likelihood analysis Of animal MovemENT behavior Using multivariate Hidden Markov Models

Get started with the vignette: Guide to using momentuHMM

Installation instructions

CRAN release

The package is available at . To install it:

install.packages("momentuHMM")

Install from Github

To install the latest (stable) version of the package from Github:

library(remotes)
install_github("bmcclintock/momentuHMM")

To install the latest (unstable) version of the package from Github:

library(remotes)
install_github("bmcclintock/momentuHMM@develop")

References

McClintock, B.T., Michelot, T. (2018) momentuHMM: R package for generalized hidden Markov models of animal movement. Methods in Ecology and Evolution, 9(6), 1518-1530.

McClintock, B.T., King R., Thomas L., Matthiopoulos J., McConnell B.J., Morales J.M. (2012) A general discrete-time modeling framework for animal movement using multistate random walks. Ecological Monographs, 82(3), 335-349.

McClintock, B.T. (2017) Incorporating telemetry error into hidden Markov models of animal movement using multiple imputation. Journal of Agricultural, Biological, and Environmental Statistics, 22(3), 249-269.

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Version

Install

install.packages('momentuHMM')

Monthly Downloads

3,895

Version

1.5.7

License

GPL-3

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/bmcclintock/momentuHMM

Homepage

https://github.com/bmcclintock/momentuHMM/discussions

Maintainer

Brett T McClintock

Last Published

October 21st, 2025

Functions in momentuHMM (1.5.7)

Constructor of crwData objects

Bernoulli density function

Fit and predict tracks for using crawl

Constructor of crwSim objects

Convert standard direction angles (in radians relative to the x-axis) to turning angle covariates suitable for circular-circular regression on the angle mean

Merge crwData or crwHierData object with additional data streams and/or covariates

Exponential density function

Gamma density function

Normal density function

negative binomial density function

Constructor of crwHierData objects

C++ implementation of multivariate Normal probability density function for multiple inputs

Constructor of crwHierSim objects

logistic density function

Probability density function of the beta distribution (written in C++)

Log-normal density function

Calculate distance between points y and z and turning angle between points x, y, and z

Get starting values from momentuHMM, miHMM, or miSum object returned by fitHMM, MIfitHMM, or MIpool

Get design matrix

dwrpcauchy_rcpp

Wrapped Cauchy density function

Categorical density function

student t density function

Poisson density function

Example dataset

Get names of any covariates used in probability distribution parameters

Convert hierarchical HMM structure to a conventional HMM

Expand vector of free working parameters to vector of all working parameters including any fixed parameters (used in fitHMM.R and nLogLike.R)

Fit a multivariate HMM to the data

is.momentuHMMData

Is momentuHMMData

Mixture probabilities

Negative log-likelihood function

Transition probability matrix

Constructor of momentuHMM objects

Negative log-likelihood

is.momentuHierHMMData

Is momentuHierHMMData

momentuHierHMMData

Constructor of momentuHierHMMData objects

Scaling function: natural to working parameters.

is.momentuHierHMM

Is momentuHierHMM

Get starting values for new model from existing momentuHMM or momentuHierHMM model fit

Forward log-probabilities

Plot observations on raster image

Get starting values on working scale based on design matrix and other parameter constraints

Plot pseudo-residuals

Plot observations on satellite image

Preprocessing of the data streams and covariates

Plot stationary state probabilities

Stationary state probabilities

Von Mises density function

Set modelName for a momentuHMM, miHMM, HMMfits, or miSum object

Random effects estimation

plot.momentuHMM

Plot momentuHMM

Constructor of miSum objects

Weibull density function

Pseudo-residuals

Constructor of miHMM objects

Parameters definition

Scaling function: working to natural parameters

print.momentuHMM

Print momentuHMM

plot.momentuHMMData

Plot momentuHMMData or momentuHierHMMData

State probabilities

Viterbi algorithm

Observation error simulation tool

Constructor of momentuHMMData objects

Backward log-probabilities

Simulation tool

summary.momentuHMMData

Summary momentuHMMData

Constructor of momentuHierHMM objects

Transition probability matrix

Calculate proportion of time steps assigned to each state (i.e. “activity budgets”)

Set stateNames for a momentuHMM, miHMM, HMMfits, or miSum object

Check parameter length and order for a fitHMM (or MIfitHMM) model

Calculate pooled parameter estimates and states across multiple imputations

Constructor of HMMfits objects

Confidence intervals for working (i.e., beta) parameters

Matrix of all probabilities

Fit HMMs to multiple imputation data

Calculate Akaike information criterion model weights

Confidence intervals for the natural (i.e., real) parameters