data(hare)
desc <- descriptive(hare)
plot(desc)
# The fi plot shows that the two animals caught on all occasions create
# some heterogeneity in the capture probabilities.
closedp(hare)
# The best fitting model Mth Poisson2(N = 81.1, s.e.=5.7) has an AIC of 146.
closedpCI.t(hare, m = "Mth", h = "Poisson", h.control = list(theta = 2))
# One can compare the fit of this model with that obtained by removing the
# 2 hares caught 6 times. This can be done by adding a column to the design
# matrix for Mt taking the value 1 for the capture history (1,1,1,1,1,1).
col <- rep(0, 2^6-1)
mat <- histpos.t(6)
col[apply(mat, 1 ,sum) == 6] <- 1
closedpCI.t(hare, mX=cbind(mat, col), mname="Mt without 111111")
# This gives N = 76.8 (s.e.=3.9) with an AIC of 146.
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