Below is an excerpt from the book Introduction to statistical learning in R, (chapter-linear model selection and regularization)
"In ridge regression, each least squares coefficient estimate is shrunken by the same proportion"
On a simple dataset, I obtained 2 non-intercept coefficients b1=-0.03036156 and b2=-0.02481822 using OLS. On l2 shrinkage with lambda=1, the new coefficients were b1=-0.01227141 and b2=-0.01887098. Both haven't reduced by equal proportions. What am I missing here?
- the assumption made in an Introduction to Statistical Learning book for the quoted statement is n=p
- the scale of both variables in my dataset is same