Total shrinkage versus partial shrinkage in multiple linear regression

Abstract

The paper discusses the merits of partial shrinkage of the ordinary least square estimator of the coefficients of the multiple regression model of full rank. Theoretical comparisons of scalar and matrix-valued risks of the partially shrunken and totally shrunken estimators are given. The strategy of partial shrinkage is applied to two data sets.

SINET: Ethiopian Journal of Science Vol. 23, No. 1 (June 2000), pp. 67-72



Key words/phrases: Partial and total shrinkage, variance inflation factors