Accession Number:

ADA064838

Title:

Nonstochastic Techniques for Selecting Ridge Parameter Values.

Descriptive Note:

Interim rept.,

Corporate Author:

SOUTHERN METHODIST UNIV DALLAS TEX DEPT OF STATISTICS

Personal Author(s):

Report Date:

1978-01-01

Pagination or Media Count:

25.0

Abstract:

Biased regression estimators are increasingly being utilized as alternatives to least square parameter estimators in multiple linear regression when the predictor variables are multicollinear. One popular biased estimator is the ridge regression estimator. Ridge estimators are known to have smaller mean squared errors than least squares for suitably small nonstochastic choices of the ridge parameter. To date, however, most of the practical applications of ridge regression employ stochastic techniques to select the ridge parameter. In this paper we examine three non stochastic procedures for choosing ridge parameters and compare their performance with another stochastic method. Author

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE