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moveHMM (version 1.1)

Animal Movement Modelling using Hidden Markov Models

Description

Provides tools for animal movement modelling using hidden Markov models. These include processing of tracking data, fitting HMMs to movement data, visualization of data and fitted model, decoding of the state process...

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Version

Install

install.packages('moveHMM')

Monthly Downloads

752

Version

1.1

License

GPL-3

Issues

0

Pull Requests

0

Stars

43

Forks

15

Maintainer

Theo Michelot

Last Published

December 2nd, 2015

Functions in moveHMM (1.1)

dwrpcauchy_rcpp

Wrapped Cauchy density function
AIC.moveHMM

AIC
plot.moveData

Plot moveData
fitHMM

Fit an HMM to the data
viterbi

Viterbi algorithm
w2n

Scaling function: working to natural parameters
nLogLike

Negative log-likelihood function
angleCI

Confidence intervals for angle parameters
example

Example dataset
prepData

Preprocessing of the tracking data
print.moveHMM

Print moveHMM
summary.moveData

Summary moveData
dvm_rcpp

Von Mises density function
CI

Confidence intervals
dweibull_rcpp

Weibull density function
moveData

Constructor of moveData objects
dexp_rcpp

Exponential density function
pseudoRes

Pseudo-residuals
moveHMM

Constructor of moveHMM objects
allProbs

Matrix of all probabilities
dgamma_rcpp

Gamma density function
logBeta

Backward log-probabilities
parDef

Parameters definition
plotPR

Plot pseudo-residuals
is.moveHMM

Is moveHMM
plot.moveHMM

Plot moveHMM
turnAngle

Turning angle
exGen

Example data simulation
logAlpha

Forward log-probabilities
simData

Simulation tool
trMatrix_rcpp

Transition probability matrix
dlnorm_rcpp

Log-normal density function
n2w

Scaling function: natural to working parameters.
plotStates

Plot states
stateProbs

State probabilities
is.moveData

Is moveData
nLogLike_rcpp

Negative log-likelihood