Ridge Regression: Biased Estimation for Nonorthogonal Problems
Arthur E. HoerlUniversity of Delaware and E. 1. du Pont de Nemours & CoRobert W. KennardUniversity of Delaware
1970en
ABI
Abstract
In multiple regression it is shown that parameter estimates based on minimum residual sum of squares have a high probability of being unsatisfactory, if not incorrect, if the prediction vectors are not orthogonal. Proposed is an estimation procedure based on adding small positive quantities to the diagonal of X′X. Introduced is the ridge trace, a method for showing in two dimensions the effects of nonorthogonality. It is then shown how to augment X′X to obtain biased estimates with smaller mean square error.
Identifiers
Citations and references
Cited by 40 references