fitList {unmarked}

constructor of unmarkedFitList objects

Description

Organize models for model selection or model-averaged prediction.

Usage

fitList(..., fits, autoNames=c("object", "formula"))

Arguments

...

Fitted models. Preferrably named.

fits

An alternative way of providing the models. A (preferrably named) list of fitted models.

autoNames

Option to change the names unmarked assigns to models if you don't name them yourself. If autoNames="object", models in the fitList will be named based on their R object names. If autoNames="formula", the models will instead be named based on their formulas. This is not possible for some model types.

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 [e-mail]

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)

## 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")