mnllTCRW: Maximum likelihood estimation of the TCRW

In MarieAugerMethe/CCRWvsLW: Searching strategy movement models

Description

Minimize the negative log-likelihood for the TCRW.

Usage

mnllTCRW(SL, TA_C, TA, SLmin=min(SL), SLmax=max(SL),
    lambda = exp(nlm(nllTBW, log(1/mean(SL - SLmin)), 
    SL = SL, TA = TA, SLmin = SLmin, SLmax = SLmax)$estimate), 
    kapp = mle.vonmises(TA_C, mu = circular(0))$kappa)
nllTCRW(SL, TA, lambda, kapp, SLmin=min(SL), SLmax=max(SL))

Arguments

SL	numeric vector containing the step lengths
TA_C	circular object containing the turning angles
TA	numeric vector containing the turning angles
SLmin	one numeric value representing the minimum step length
SLmax	one numeric value representing the maximum step length
lambda	one numeric value for lambda value, the default MLE for the TBW
kapp	one numeric value for kappa value, the default MLE for the CRW

Details

The mnllTCRW function minimize the negative log likelihood using the default formula in the input to get the estimates. It returns parameter estimates, the negative log likelihood, AIC, and AICc.

The nllTCRW 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 <- simmCRW(500,0.1,5,1)
formPath <- movFormat(simPath)
mnllCRW(formPath$SL, formPath$TA_C, formPath$TA, formPath$SLmin)

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