Tidy a(n) smooth.spine object

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.

See also

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

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

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.

Examples

if (FALSE) {

# 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))
}