Description Usage Arguments Value See Also Examples
This function estimates abundance and related parameters from a mark recapture method sample object (of class ‘sample.cr’), using the mark recapture model Mt.
1 | point.est.crMt(samp.cr, init.N = -1)
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sample |
object of class 'sample.cr.´ |
init.N |
starting value of N used in maximum likelihood optimisation routine |
An object of class 'point.est.crMt´ containing the following items:
sample |
details of the object of class 'sample.cr', used to create the sample |
Nhat.grp |
MLE of group abundance |
Nhat.ind |
MLE of individual abundance (= Nhat.grp * Es) |
phat |
Estimate(s) of capture probability for the relevant model (try it and see) |
Es |
Estimate of mean group size (simple mean of observed group sizes) |
log.Likelihood |
Value of log-likelihood at MLE |
res.Deviance |
Residual deviance at MLE |
AIC |
Akaike's information criterion |
init.N |
starting value of N used in maximum likelihood optimisation routine |
parents |
Details of WiSP objects passed to function |
created |
Creation date and time |
setpars.survey.cr
, generate.sample.cr
int.est.crMt
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | cr.reg<-generate.region(x.length=100, y.width=50)
cr.dens <- generate.density(cr.reg)
cr.poppars<-setpars.population(density.pop = cr.dens, number.groups = 100,
size.method = "poisson", size.min = 1, size.max = 5,
size.mean = 1, exposure.method = "beta", exposure.min = 2,
exposure.max = 10, exposure.mean = 3, exposure.shape = 0.5,
type.values = c("Male","Female"), type.prob = c(0.48,0.52))
cr.pop<-generate.population(cr.poppars)
cr.des<-generate.design.cr(cr.reg, n.occ = 4)
cr.survpars<-setpars.survey.cr(cr.pop, cr.des, pmin.unmarked=0.00001, pmax.unmarked=0.5, improvement=0.01)
cr.samp<-generate.sample.cr(cr.survpars)
# Mt
cr.est.Mt<-point.est.crMt(cr.samp)
summary(cr.est.Mt)
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