laake.a: Laake's availability correction factor calculation for...

Description Usage Arguments Details References See Also Examples

Description

Calculates the probability that an animal is available at least once while within detectable region, using the method of Laake et al. (1997), Eqn (4). Does this for each of a set of m 2-state Markov model availability parameters passed to it and returns probabilities and their mean.

Usage

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laake.a(hmm.pars, ymax, spd = NULL)

Arguments

hmm.pars

is a list with 2x2xm Markov model transition matrices (in which state 1 is UNavailable) in element $Pi (where m is number of availability parameter sets).

ymax

is maximum forward distance to consider (‘w’ in Laake et al. (1997), Eqn (4)).

spd

speed of observer. Needed to convert time (units of hmm.pars) to distance (units of ymax).

Details

See Laake et al. (1997), Eqn (4), or Borchers et al. (2013) for details of Laake's method.

References

Borchers, D.L., Zucchini, W., Heide-Jorgenssen, M.P., Canadas, A. and Langrock, R. 2013. Using hidden Markov models to deal with availability bias on line transect surveys. Biometrics.

Laake, J., Calambokidis, J., Osmek, S., and Rugh, D. 1997. Probability of detecting harbor porpoise from aerial surveys: estimating g(0). Journal of Wildlife Management 61, 63-75.

See Also

instant.a, mclaren.a, richard.a

Examples

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Ea=c(10,12);Eu=c(20,22);seEa=c(2,3);seEu=c(4,6);covEt=c(2,3)
hmm.pars=make.hmm.pars.from.Et(Ea,Eu,seEa,seEu,covEt)
laake.a(hmm.pars,ymax=200,spd=4) # because hmm.pars is in units of time, not distance, you need to specify spd.

DistanceDevelopment/hsltm documentation built on June 21, 2019, 2:22 p.m.