summary: Summarize mcsSubset objects

In mcsSubset: MCS: Variable Subset Selection in Linear Regression

Description

Summary methods for objects of class mcsSubset.

Usage

## S3 method for class 'mcsSubset'
summary(object, penalty = 2, ...)

Arguments

object	An object of class mcsSubset.
penalty	The AIC penalty.
...	Ignored.

Details

The summary method for mcsSubset objects computes the AIC for the desired penalty.

Value

An object of class summary.mcsSubset. The subset models contained in the summary object are sorted in order of increasing AIC.

Extractor methods may be called on summary objects to obtain information about the best subset models. See methods for more details.

See Also

mcsSubset, methods.

Examples

## load data
data("AirPollution", package = "mcsSubset")

## fit best subsets
xs <- mcsSubset(mortality ~ ., data = AirPollution)

## summarize (BIC)
sx <- summary(xs, penalty = log(nrow(AirPollution)))
sx

## refit (best BIC)
lm <- refit(sx)
summary(lm)

## refit (second best BIC)
lm <- refit(sx, best=2)
summary(lm)

mcsSubset documentation built on May 2, 2019, 6:50 p.m.