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moveHMM (version 1.0)

Animal Movement Modelling using Hidden Markov Models

Description

Animal movement modelling using hidden Markov models. Pre-processing of tracking data, fitting HMMs to movement data, visualization of data and fitted model...

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Version

Install

install.packages('moveHMM')

Monthly Downloads

786

Version

1.0

License

GPL-3

Maintainer

Theo Michelot

Last Published

October 23rd, 2015

Functions in moveHMM (1.0)

CI

Confidence intervals
fitHMM

Fit an HMM to the data
moveHMM

Constructor of moveHMM objects
logBeta

Backward log-probabilities
allProbs

Matrix of all probabilities
dexp_rcpp

Exponential density function
simData

Simulation tool
trMatrix_rcpp

Transition probability matrix
moveData

Constructor of moveData objects
nLogLike

Negative log-likelihood function
n2w

Scaling function: natural to working parameters.
plotStates

Plot states
plot.moveHMM

Plot moveHMM
logAlpha

Forward log-probabilities
dweibull_rcpp

Weibull density function
summary.moveData

Summary moveData
stateProbs

State probabilities
AIC.moveHMM

AIC
prepData

Preprocessing of the tracking data
dgamma_rcpp

Gamma density function
viterbi

Viterbi algorithm
is.moveHMM

Is moveHMM
dlnorm_rcpp

Log-normal density function
is.moveData

Is moveData
dvm_rcpp

Von Mises density function
exGen

Example data simulation
example

Example dataset
plot.moveData

Plot moveData
nLogLike_rcpp

Negative log-likelihood
parDef

Parameters definition
turnAngle

Turning angle
print.moveHMM

Print moveHMM
w2n

Scaling function: working to natural parameters
dwrpcauchy_rcpp

Wrapped Cauchy density function
angleCI

Confidence intervals for angle parameters
plotPR

Plot pseudo-residuals
pseudoRes

Pseudo-residuals