## Not run: ------------------------------------
#
# # Generate some detection and telemetry data, combine them using
# # addTelemetry, and perform analyses
#
# # detectors
# te <- make.telemetry()
# tr <- make.grid(detector = "proximity")
#
# # simulated population and 50% telemetry sample
# totalpop <- sim.popn(tr, D = 20, buffer = 100)
# tepop <- subset(totalpop, runif(nrow(totalpop)) < 0.5)
#
# # simulated detection histories and telemetry
# # the original animalID (renumber = FALSE) are needed for matching
# trCH <- sim.capthist(tr, popn = totalpop, renumber = FALSE, detectfn = "HHN")
# teCH <- sim.capthist(te, popn = tepop, renumber=FALSE, detectfn = "HHN",
# detectpar = list(lambda0 = 3, sigma = 25))
#
# combinedCH <- addTelemetry(trCH, teCH)
#
# # summarise and display
# summary(combinedCH)
# plot(combinedCH, border = 150)
# ncapt <- apply(combinedCH,1,sum)
# points(totalpop[row.names(combinedCH)[ncapt==0],], pch = 1)
# points(totalpop[row.names(combinedCH)[ncapt>0],], pch = 16)
#
# # for later comparison of precison we must fix the habitat mask
# mask <- make.mask(tr, buffer = 100)
# fit.tr <- secr.fit(trCH, mask = mask, CL = TRUE, detectfn = "HHN") ## trapping alone
# fit.te <- secr.fit(teCH, mask = mask, CL = TRUE, start = log(20), ## telemetry alone
# detectfn = "HHN")
# fit2 <- secr.fit(combinedCH, mask = mask, CL = TRUE, ## combined
# detectfn = "HHN")
#
# # improved precision when focus on realised population
# # (compare CVD)
# derived(fit.tr, distribution = "binomial")
# derived(fit2, distribution = "binomial")
#
#
# # may also use CL = FALSE
# secr.fit(combinedCH, CL = FALSE, detectfn = "HHN", trace = FALSE)
## ---------------------------------------------
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