Ridge Regression: Degrees of Freedom in the Analysis of Variance

Abstract

It appears to be common practice with ridge regression to obtain a decomposition of the total sum of squares, and assign degrees of freedom, according to established least squares theory. This discussion notes the obvious fallacies of such an approach, and introduces a decomposition based on orthogonality, and degrees of freedom based on expected mean squares, for non-stochastic k.

Keywords:

• ridge regression
• degrees of freedom
• orthogonal decomposition
• analysis of variance