MuMIn (version 1.48.4)

get.models: Retrieve models from selection table

Description

Generate or extract a list of fitted model objects from a "model.selection" table or component models from the averaged model ("averaging" object), optionally using parallel computation in a cluster.

Usage

get.models(object, subset, cluster = NA, ...)

Value

list of fitted model objects.

Arguments

object

object returned by dredge, model.sel or model.avg.

subset

subset of models, an expression evaluated within the model selection table (see ‘Details’).

cluster

optionally, a "cluster" object. If it is a valid cluster, models are evaluated using parallel computation.

...

additional arguments to update the models. For example, one may want to fit models with REML (e.g. argument REML = TRUE in some modelling functions) while using ML for model selection.

Author

Kamil Bartoń

Details

The argument subset must be explicitely provided. This is to assure that a potentially long list of models is not fitted unintentionally. To evaluate all models, set subset to NA or TRUE.

If subset is a character vector, it is interpreted as names of rows to be selected.

See Also

dredge and pdredge, model.avg

makeCluster in packages parallel and snow

Examples

# Mixed models:

 if(require(nlme)) { 
fm2 <- lme(distance ~ age + Sex, data = Orthodont,
    random = ~ 1 | Subject, method = "ML")
ms2 <- dredge(fm2)

# Get top-most models, but fitted by REML:
(confset.d4 <- get.models(ms2, subset = delta < 4, method = "REML"))

if (FALSE) {
# Get the top model:
get.models(ms2, subset = 1)[[1]]
}

  }