modSel {unmarked} | R Documentation |
Model selection on a list of unmarked
model fits
Description
Model selection results from an unmarkedFitList
Arguments
object |
an object of class "unmarkedFitList" created by the function
|
nullmod |
optional character naming which model in the
|
Value
An object of class unmarkedModSel
.
Note
Two requirements exist to conduct AIC-based model-selection and model-averaging in unmarked. First, the data objects (ie, unmarkedFrames) must be identical among fitted models. Second, the response matrix must be identical among fitted models after missing values have been removed. This means that if a response value was removed in one model due to missingness, it needs to be removed from all models.
Author(s)
Richard Chandler rbchan@uga.edu
References
Nagelkerke, N.J.D. (2004) A Note on a General Definition of the Coefficient of Determination. Biometrika 78, pp. 691-692.
See Also
Examples
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)
fl <- fitList(Null=fm1, A.=fm2, .A=fm3)
fl
ms <- modSel(fl, nullmod="Null")
ms
coef(ms) # Estimates only
SE(ms) # Standard errors only
(toExport <- as(ms, "data.frame")) # Everything