mnllBW: Maximum likelihood estimation of the BW

Description Usage Arguments Details References Examples

Description

Minimize the negative log-likelihood for the BW.

Usage

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mnllBW(SL, TA, SLmin=min(SL))
nllBW(SL,TA,lambda,parF=list('SLmin'=min(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 min(SL)

lambda

one numeric value for lambda

parF

list for fix parameter values, see default

Details

The mnllBW function uses an analytical solution to maximize the likelihood to estimate the parameters.

The nllBW 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

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simPath <- simmBW(500,0.1,1)
formPath <- movFormat(simPath)
mnllBW(formPath$SL, formPath$TA, formPath$SLmin)

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