lmSubsets (version 0.5-1)

methods: Methods for 'lmSubsets' and 'lmSelect' Objects

Description

Extractor methods for "lmSubsets" and "lmSelect" objects.

Usage

# S3 method for lmSubsets
variable.names(object, size, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
variable.names(object, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
formula(x, size, best = 1, …)
# S3 method for lmSelect
formula(x, best, …)
# S3 method for lmSubsets
model.frame(formula, …)
# S3 method for lmSelect
model.frame(formula, …)
# S3 method for lmSubsets
model.matrix(object, size, best = 1, …)
# S3 method for lmSelect
model.matrix(object, best, …)
# S3 method for lmSubsets
model_response(data, …)
# S3 method for lmSelect
model_response(data, …)
# S3 method for lmSubsets
refit(object, size, best = 1, …)
# S3 method for lmSelect
refit(object, best = 1, …)
# S3 method for lmSubsets
deviance(object, size, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
deviance(object, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
sigma(object, size, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
sigma(object, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
logLik(object, size, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
logLik(object, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
AIC(object, size, best = 1, …, k = 2, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
AIC(object, best = 1, …, k = 2, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
BIC(object, size, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
BIC(object, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
coef(object, size, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSelect
coef(object, best = 1, …, na.rm = TRUE, drop = TRUE)
# S3 method for lmSubsets
vcov(object, size, best = 1, …)
# S3 method for lmSelect
vcov(object, best = 1, …)
# S3 method for lmSubsets
fitted(object, size, best = 1, …)
# S3 method for lmSelect
fitted(object, best = 1, …)
# S3 method for lmSubsets
residuals(object, size, best = 1, …)
# S3 method for lmSelect
residuals(object, best = 1, …)

Arguments

object, formula, data, x

An object of class "lmSubsets" or "lmSelect".

size

The submodel size.

best

The submodel ranking.

…

Forwarded arguments.

k

AIC penalty.

drop

Control shape of return value.

na.rm

Remove missing submodels.

Details

The extractor methods work for "lmSubsets" and "lmSelect" objects, i.e., objects that have been generated using the formula interface.

If drop == FALSE, the extractor methods variable.names, deviance, sigma, logLik, AIC, BIC and coef return a data.frame object. If drop == TRUE, the return value is a logical matrix (variable.names), a numeric matrix (coef), or a numeric vector. If the drop parameter is not set explicitly when calling variable.names or coef, one-dimensional values are represented in a compact form.

If a desired extractor function is not available, refit can be called explicitly to obtain the corresponding "lm" object.

See Also

lmSubsets, lmSelect, refit.

Examples

# NOT RUN {
## load data
data("AirPollution", package = "lmSubsets")

## fit subsets (5 best subsets per size)
lm_all <- lmSubsets(mortality ~ ., data = AirPollution, nbest = 5)

## extract information (for best submodel of size 3)
coef(lm_all, size = 3)
vcov(lm_all, size = 3)
residuals(lm_all, size = 3)
fitted(lm_all, size = 3)
model.matrix(lm_all, size = 3)

## select best (BIC) submodels
lm_best <- lmSelect(lm_all)

## extract information
deviance(lm_best)
logLik(lm_best)
AIC(lm_best)
BIC(lm_best, best = 1:5)

## refit model
lm5 <- refit(lm_all, size = 5)
summary(lm5)
## (Note that the p-values are not valid due to model selection.)
# }