Tidy a(n) ridgelm 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.
## S3 method for class 'ridgelm' tidy(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 columns:
GCV |
Generalized cross validation error estimate. |
lambda |
Value of penalty parameter lambda. |
term |
The name of the regression term. |
estimate |
estimate of scaled coefficient using this lambda |
scale |
Scaling factor of estimated coefficient |
Other ridgelm tidiers:
glance.ridgelm()
if (requireNamespace("MASS", quietly = TRUE)) {
names(longley)[1] <- "y"
fit1 <- MASS::lm.ridge(y ~ ., longley)
tidy(fit1)
fit2 <- MASS::lm.ridge(y ~ ., longley, lambda = seq(0.001, .05, .001))
td2 <- tidy(fit2)
g2 <- glance(fit2)
# coefficient plot
library(ggplot2)
ggplot(td2, aes(lambda, estimate, color = term)) +
geom_line()
# GCV plot
ggplot(td2, aes(lambda, GCV)) +
geom_line()
# add line for the GCV minimizing estimate
ggplot(td2, aes(lambda, GCV)) +
geom_line() +
geom_vline(xintercept = g2$lambdaGCV, col = "red", lty = 2)
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