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broom (version 0.7.8)

glance.smooth.spline: 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 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. 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 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

Run this code
# NOT RUN {
spl <- smooth.spline(mtcars$wt, mtcars$mpg, df = 4)
augment(spl, mtcars)
augment(spl) # calls original columns x and y

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

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