mnllLW: Maximum likelihood estimation of the LW

In MarieAugerMethe/CCRWvsLW: Searching strategy movement models

Description

Minimize the negative log-likelihood for the LW.

Usage

mnllLW(SL, TA, SLmin = min(SL))
nllLW(SL,TA,mu,parF=list('SLmin'=min(SL)))

Arguments

SL	numeric vector containing the step lengths, default min(SL)
TA	numeric vector containing the turning angles
SLmin	one numeric value representing the minimum step length
mu	one numeric value for the parameter
parF	list for fix parameter values, see default

Details

The mnllLW function uses an analytical solution to maximize the likelihood to estimate the parameter mu. Note that the parameter value is restrained between 1 and 3, if the value returned by the analytical formula is greater outside these bounds a constrained optimizer is used.

The nllLW function evaluate 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 <- simmLW(500,2,1)
formPath <- movFormat(simPath)
mnllLW(formPath$SL, formPath$TA)

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