broom (version 0.8.0)

tidy.regsubsets: Tidy a(n) regsubsets object

Description

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

# S3 method for regsubsets
tidy(x, ...)

Arguments

x

A regsubsets object created by leaps::regsubsets().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

Value

A tibble::tibble() with columns:

r.squared

R squared statistic, or the percent of variation explained by the model.

adj.r.squared

Adjusted R squared statistic

BIC

Bayesian information criterion for the component.

mallows_cp

Mallow's Cp statistic.

See Also

tidy(), leaps::regsubsets()

Examples

# NOT RUN {
# feel free to ignore the following line<U+2014>it allows {broom} to supply 
# examples without requiring the model-supplying package to be installed.
if (requireNamespace("leaps", quietly = TRUE)) {

# load libraries for models and data
library(leaps)

# fit model
all_fits <- regsubsets(hp ~ ., mtcars)

# summarize model fit with tidiers
tidy(all_fits)

}

# }