glance.smooth.spline {broom}

Tidy a(n) smooth.spine 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 class 'smooth.spline'
glance(x, ...)

Arguments

x

A smooth.spline object returned from stats::smooth.spline().

...

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. Two exceptions here are:

• tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

• augment() methods will warn when supplied a newdata argument if it will be ignored.

Value

A tibble::tibble() with exactly one row and columns:

crit

Minimized criterion

cv.crit

Cross-validation score

df

Degrees of freedom used by the model.

lambda

Choice of lambda corresponding to 'spar'.

nobs

Number of observations used.

pen.crit

Penalized criterion.

spar

Smoothing parameter.

See Also

augment(), stats::smooth.spline()

Other smoothing spline tidiers: augment.smooth.spline()

Examples

# fit model
spl <- smooth.spline(mtcars$wt, mtcars$mpg, df = 4)

# summarize model fit with tidiers
augment(spl, mtcars)

# calls original columns x and y
augment(spl)

library(ggplot2)
ggplot(augment(spl, mtcars), aes(wt, mpg)) +
  geom_point() +
  geom_line(aes(y = .fitted))