View source: R/stats-smooth.spline-tidiers.R
glance.smooth.spline | R Documentation |
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 class 'smooth.spline'
glance(x, ...)
x |
A |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in
|
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. |
augment()
, stats::smooth.spline()
Other smoothing spline tidiers:
augment.smooth.spline()
# 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))
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