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

In david-borchers/hmltm: Line transect estimation with hidden Markov availability models

Laake's availability correction factor calculation for multiple availability models.

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

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

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.

david-borchers/hmltm documentation built on Oct. 29, 2023, 9:07 p.m.