secr (version 2.9.0)

fx.total: Activity Centres of Detected and Undetected Animals

Description

The summed probability densities of both observed and unobserved individuals are computed for a fitted model and dataset.

Usage

fx.total(object, sessnum = 1, mask = NULL, ...)

Arguments

object

a fitted secr model

sessnum

session number if object$capthist spans multiple sessions

mask

x- and y- coordinates of points at which density will be computed

...

other arguments passed to detectpar and thence to predict.secr

Value

• An object of class `Dsurface' (a variety of mask) with a `covariates' attribute that is a dataframe with columns --
• D.fx
  sum of fxi over all detected individuals
• D.nc
  expected density of undetected (`not caught') individuals
• D.sum
  sum of D.fx and D.nc
• All densities are in animals per hectare (the `scale' argument of plot.Dsurface allows the units to be varied later).

Details

This function calls fxi.secr for each detected animal and overlays the results to obtain a summed probability density surface D.fx for the locations of the home-range centres of detected individuals. A separate calculation using pdot provides the expected spatial distribution of undetected animals, as another density surface: crudely, D.nc(X) = D(X) * ( 1 -- pdot(X)). The pointwise sum of the two surfaces is sometimes used to represent the spatial distrbution of the population, but see Notes.

References

Borchers, D. L. and Efford, M. G. (2008) Spatially explicit maximum likelihood methods for capture--recapture studies. Biometrics 64, 377--385.

See Also

fxi.secr, fxi.contour, pdot

Examples

tmp <- fx.total(secrdemo.0)
plot(tmp, covariate = 'D.sum', col = terrain.colors(16),
   plottype = 'shaded')
plot(tmp, covariate = 'D.sum', col = 'white', add = TRUE,
   plottype = 'contour')
spotHeight(tmp, prefix = 'D.sum')