data(deermouse)
capthist
objects
`deermouse.ESG' and `deermouse.WSG'. Each has a dataframe of individual
covariates, but the fields differ between the two study areas. The
individual covariates of deermouse.ESG are sex (factor levels `f', `m'),
age class (factor levels `y', `sa', `a') and body weight in grams. The
individual covariates of deermouse.WSG are sex (factor levels `f',`m')
and age class (factor levels `j', `y', `sa', `a') (no data on body
weight). The aging criteria used by Reid are not recorded.
The datasets were originally in the CAPTURE `xy complete' format which
for each detection gives the `column' and `row' numbers of the trap
(e.g. ` 9 5' for a capture in the trap at position (x=9, y=5) on the
grid). Trap identifiers have been recoded as strings with no spaces by
inserting zeros (e.g. `905' in this example).
Sherman traps are designed to capture one animal at a time, but the data
include double captures (1 at ESG and 8 at WSG -- see Examples). The true
detector type therefore falls between `single' and `multi'. Detector
type is set to `multi' in the distributed data objects.
Some fitted secr
models are included (ESG.0, ESG.b, ESG.t, ESG.h2,
WSG.0, WSG.b, WSG.t, WSG.h2, each with the indicated effect on g0). Otis
et al. (1978) draw attention to the tendency of Peromyscus to become
`trap happy', and we observe that models with a behavioural response
(ESG.b, WSG.b) have the lowest AIC among those fitted here.
closure.test
par(mfrow = c(1,2), mar = c(1,1,4,1))
plot(deermouse.ESG, title = "Peromyscus data from East Stuart Gulch",
border = 10, gridlines = FALSE, tracks = TRUE)
plot(deermouse.WSG, title = "Peromyscus data from Wet Swizer Gulch",
border = 10, gridlines = FALSE, tracks = TRUE)
closure.test(deermouse.ESG, SB = TRUE)
## reveal multiple captures
table(trap(deermouse.ESG), occasion(deermouse.ESG))
table(trap(deermouse.WSG), occasion(deermouse.WSG))
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