Description Usage Arguments Details Examples
Calculates the probability density function for the estimated
location of one or more range centres, i.e. f(X  Ω). Acts as a
wrapper function for fxi.secr
.
1 2 
fit 
a fitted secrgam model (returned from

i 
integer or character vector of individuals for which to plot contours 
col 
integer or character vector of colour for individuals' contours 
X 
2column matrix of x and y coordinates (e.g. the original mask) 
plt 
logical to do contour plot 
add 
logical to add to existing plot 
sessnum 
session number if 
border 
width of blank margin around the outermost detectors 
normal 
logical; should values of pdf be normalised? 
... 
additional arguments passed to contour. 
fxi.secr
returns a vector of probability densities assuming a
uniform density distribution,
f(x_i  ω_i) = P(ω_i  x_i) / ∑ P(ω_i  x_i)
fxi.secrgam
returns a vector of probability densities for any
density distribution,
f(x_i  ω_i) = P(ω_i  x_i) D(x_i) / ∑ [ P(ω_i  x_i) D(x_i) ]
Needs to be tested for cases where density model has fixed parameters. Also assumes that log link is used for density.
1 2 3 4 5 6 7 8 9 10  data(Boland.fits1)
# capture history data
plot(fit1.a3$capthist)
# look at data for animal 20
animal = 20
k = apply(fit1.a3$capthist[animal,,], 2, sum) > 0
points(traps(fit1.a3$capthist)[k,], col = 2, pch = 19)
fxi.secrgam(fit1.a3, i = animal, add = TRUE)

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