setwd('d:\density communication\webtest\foxton\')
possumtraps <- read.traps(file = 'foxtraps.txt', detector = 'single')
temp <- read.captures('foxton.txt', colClasses=c('character',
'character', 'numeric', 'character'))
## drop within-day duplicates of animal 5861
temp <- temp[-c(184,186),]
possumCH <- make.capthist(temp, possumtraps)
possummask <- make.mask(possumtraps, buffer = 300, type='pdot',
pdotmin = 0.001, detectpar = list(g0=0.2, sigma=60), spacing = 10)
## fit constant-density model
possum.model.1 <- secr.fit(possumCH, mask = possummask)
## fit learned trap response model
possum.model.1b <- secr.fit(possumCH, mask = possummask, model = list(g0~b))
require (graphics)
data(possum)
plot(possummask)
plot(possumCH, tracks = TRUE, add = TRUE)
plot(traps(possumCH), add = TRUE)
summary(possumCH)
## compare & average pre-fitted models
AIC(possum.model.1, possum.model.1b)
model.average(possum.model.1, possum.model.1b)
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