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.
# S3 method for regsubsets
tidy(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.level = 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.
A tibble::tibble()
with columns:
R squared statistic, or the percent of variation explained by the model.
Adjusted R squared statistic
Bayesian information criterion for the component.
Mallow's Cp statistic.
# NOT RUN {
all_fits <- leaps::regsubsets(hp ~ ., mtcars)
tidy(all_fits)
# }
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