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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(devtools)
install_github("bmcclintock/momentuHMM")

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

library(devtools)
install_github("bmcclintock/momentuHMM", ref="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

625

Version

1.4.3

License

GPL-3

Maintainer

Brett T McClintock

Last Published

November 22nd, 2018

Functions in momentuHMM (1.4.3)

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

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

Fit and predict tracks for using crawl

Constructor of crwData objects

Merge crwData object with additional data streams and/or covariates

Exponential density function

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

Example data simulation

Fit HMMs to multiple imputation data

Example dataset

Calculate Akaike information criterion model weights

Constructor of crwSim objects

Calculate pooled parameter estimates and states across multiple imputations

Forward log-probabilities

Bernoulli density function

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

plot.momentuHMMData

Plot momentuHMMData

Backward log-probabilities

Fit a multivariate HMM to the data

Gamma density function

Weibull density function

Poisson density function

Von Mises density function

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

Plot pseudo-residuals

Get starting values for new model from existing momentuHMM model fit

Constructor of momentuHMM objects

dwrpcauchy_rcpp

Wrapped Cauchy density function

Constructor of miHMM objects

Constructor of momentuHMMData objects

Negative log-likelihood

Constructor of miSum objects

Get names of any covariates used in probability distribution parameters

Plot observations on satellite image

Log-normal density function

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

Plot observations on raster image

Get design matrix

Parameters definition

Normal density function

Simulation tool

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

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

Transition probability matrix

Plot stationary state probabilities

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

is.momentuHMMData

Is momentuHMMData

Stationary state probabilities

Preprocessing of the data streams and covariates

Negative log-likelihood function

Scaling function: natural to working parameters.

summary.momentuHMMData

Summary momentuHMMData

Scaling function: working to natural parameters

plot.momentuHMM

Plot momentuHMM

print.momentuHMM

Print momentuHMM

Observation error simulation tool

Pseudo-residuals

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

State probabilities

Viterbi algorithm

Constructor of HMMfits objects

Matrix of all probabilities

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

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