mnllTLW: Maximum likelihood estimation of the TLW

In MarieAugerMethe/CCRWvsLW: Searching strategy movement models

Description

Minimize the negative log-likelihood for the TLW.

Usage

mnllTLW(SL, TA, SLmin=min(SL), SLmax=max(SL), conts=TRUE)
nllTLW(SL,TA,mu,parF=list(SLmin=min(SL),SLmax=max(SL)))

Arguments

SL	numeric vector containing the step lengths
TA	numeric vector containing the turning angles
SLmin	one numeric value representing the minimum step length, default is the min(SL)
SLmax	one numeric value representing the maximum step length, default is the max(SL)
mu	one numeric value for parameter
parF	list for fix parameter values, see default
conts	logical value stating whether to contrain mu between 1 and 3 (i.e. the values relevant for the Levy walk searching strategy)

Details

The mnllTLW function numerically minimeze the negative log likelihood to estimate the parameter mu. Note that the parameter value is constrained between 1 and 3.

The nllTLW function evaluates the negative log likelihood value.

References

Please refer to Auger-Methe, M., A.E. Derocher, M.J. Plank, E.A. Codling, M.A. Lewis (2015-In Press) Differentiating the Levy walk from a composite correlated random walk. Methods in Ecology and Evolution. Preprint available at http://arxiv.org/abs/1406.4355

Examples

simPath <- simmTLW(500,2,1,1000)
formPath <- movFormat(simPath)
mnllTLW(formPath$SL, formPath$TA)

MarieAugerMethe/CCRWvsLW documentation built on May 7, 2019, 2:50 p.m.