momentuHMM1.5.5 package

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

AIC.momentuHMM

AIC

AICweights

Calculate Akaike information criterion model weights

allProbs

Matrix of all probabilities

checkPar0

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

CIbeta

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

circAngles

Convert standard direction angles (in radians relative to the x-axis) ...

CIreal

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

crawlMerge

Merge crwData or crwHierData object with additional data streams and/o...

crawlWrap

Fit and predict tracks for using crawl

crwData

Constructor of crwData objects

crwHierData

Constructor of crwHierData objects

crwHierSim

Constructor of crwHierSim objects

crwSim

Constructor of crwSim objects

dbern_rcpp

Bernoulli density function

dbeta_rcpp

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

dcat_rcpp

Categorical density function

dexp_rcpp

Exponential density function

dgamma_rcpp

Gamma density function

distAngle

Calculate distance between points y and z and turning angle between po...

dlnorm_rcpp

Log-normal density function

dlogis_rcpp

logistic density function

dmvnorm_rcpp

C++ implementation of multivariate Normal probability density function...

dnbinom_rcpp

negative binomial density function

dnorm_rcpp

Normal density function

dpois_rcpp

Poisson density function

dt_rcpp

student t density function

dvm_rcpp

Von Mises density function

dweibull_rcpp

Weibull density function

dwrpcauchy_rcpp

Wrapped Cauchy density function

exampleData

Example dataset

expandPar

Expand vector of free working parameters to vector of all working para...

fitHMM

Fit a multivariate HMM to the data

formatHierHMM

Convert hierarchical HMM structure to a conventional HMM

getCovNames

Get names of any covariates used in probability distribution parameter...

getDM_rcpp

Get design matrix

getPar

Get starting values from momentuHMM, miHMM, or miSum object returned b...

getPar0

Get starting values for new model from existing momentuHMM or `momen...

getParDM

Get starting values on working scale based on design matrix and other ...

getTrProbs

Transition probability matrix

HMMfits

Constructor of HMMfits objects

is.crwData

Is crwData

is.crwHierData

Is crwHierData

is.crwHierSim

Is crwHierSim

is.crwSim

Is crwSim

is.HMMfits

Is HMMfits

is.miHMM

Is miHMM

is.miSum

Is miSum

is.momentuHierHMM

Is momentuHierHMM

is.momentuHierHMMData

Is momentuHierHMMData

is.momentuHMM

Is momentuHMM

is.momentuHMMData

Is momentuHMMData

logAlpha

Forward log-probabilities

logBeta

Backward log-probabilities

MIfitHMM

Fit HMMs to multiple imputation data

miHMM

Constructor of miHMM objects

MIpool

Calculate pooled parameter estimates and states across multiple imputa...

miSum

Constructor of miSum objects

mixtureProbs

Mixture probabilities

momentuHierHMM

Constructor of momentuHierHMM objects

momentuHierHMMData

Constructor of momentuHierHMMData objects

momentuHMM

Constructor of momentuHMM objects

momentuHMMData

Constructor of momentuHMMData objects

n2w

Scaling function: natural to working parameters.

nLogLike

Negative log-likelihood function

nLogLike_rcpp

Negative log-likelihood

parDef

Parameters definition

plot.crwData

Plot crwData

plot.miHMM

Plot miHMM

plot.miSum

Plot miSum

plot.momentuHMM

Plot momentuHMM

plot.momentuHMMData

Plot momentuHMMData or momentuHierHMMData

plotPR

Plot pseudo-residuals

plotSat

Plot observations on satellite image

plotSpatialCov

Plot observations on raster image

plotStates

Plot states

plotStationary

Plot stationary state probabilities

prepData

Preprocessing of the data streams and covariates

print.miHMM

Print miHMM

print.miSum

Print miSum

print.momentuHMM

Print momentuHMM

pseudoRes

Pseudo-residuals

randomEffects

Random effects estimation

setModelName

Set modelName for a momentuHMM, miHMM, HMMfits, or miSum obj...

setStateNames

Set stateNames for a momentuHMM, miHMM, HMMfits, or miSum ob...

simData

Simulation tool

simObsData

Observation error simulation tool

stateProbs

State probabilities

stationary

Stationary state probabilities

summary.momentuHMMData

Summary momentuHMMData

timeInStates

Calculate proportion of time steps assigned to each state (i.e. activi...

trMatrix_rcpp

Transition probability matrix

turnAngle

Turning angle

viterbi

Viterbi algorithm

w2n

Scaling function: working to natural parameters

XBloop_rcpp

Get XB

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>.

  • Maintainer: Brett McClintock
  • License: GPL-3
  • Last published: 2022-10-18