data(linetran)
(dbreaksLine <- c(0, 5, 10, 15, 20))
lengths <- linetran$Length * 1000
ltUMF <- with(linetran, {
unmarkedFrameDS(y = cbind(dc1, dc2, dc3, dc4),
siteCovs = data.frame(Length, area, habitat), dist.breaks = dbreaksLine,
tlength = lengths, survey = "line", unitsIn = "m")
})
fm1 <- distsamp(~ 1 ~1, ltUMF)
fm2 <- distsamp(~ area ~1, ltUMF)
fm3 <- distsamp( ~ 1 ~area, ltUMF)
## Two methods of creating an unmarkedFitList using fitList()
# Method 1
fmList <- fitList(Null=fm1, .area=fm2, area.=fm3)
# Method 2. Note that the arugment name "fits" must be included in call.
models <- list(Null=fm1, .area=fm2, area.=fm3)
fmList <- fitList(fits = models)
# Extract coefficients and standard errors
coef(fmList)
SE(fmList)
# Model-averaged prediction
predict(fmList, type="state")
# Model selection
modSel(fmList, nullmod="Null")
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