Ridge Regression: Biased Estimation for Nonorthogonal Problems


Hoerl, Arthur E.; Kennard, Robert W.   (2000, ASQ and American Statistical Association)   University of Delaware; E. I. du Pont de Nemours & Co.

Technometrics    Vol. 42    No. 1
QICID: 13869    February 2000    pp. 80-86
List $10.00
Member $5.00

This article is not available online. Contact us to receive a scan of the archive, in PDF format.

Article Abstract

[This abstract is based on the authors' 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. The ridge trace is introduced, this being a method for demonstrating the effects of nonorthogonality in two dimensions. It then is shown how to augment X'X to obtain biased estimates with smaller mean square error.


Augmentation,Orthogonal array (OA),Multiple regression,Estimation

Browse QIC Articles Chronologically:     Previous Article     Next Article

New Search

Featured advertisers

ASQ is a global community of people passionate about quality, who use the tools, their ideas and expertise to make our world work better. ASQ: The Global Voice of Quality.