A general investigation of mean square error matrix superiority in linear regression

Gabriele Ihorst; Götz Trenkler

doi:10.6092/issn.1973-2201/996

A general investigation of mean square error matrix superiority in linear regression

Authors

Gabriele Ihorst University of Freiburg
Institute for Medical Biometry and Medical Statistics
Götz Trenkler Universität Dortmund
Department of Statistics

DOI:

https://doi.org/10.6092/issn.1973-2201/996

Abstract

Two given generalized ridge estimators of the linear regression model are compared with respect to the matrix mean square error criterion. Using a result concerning the difference of nonnegative definite matrices modified by two matrices of rank one, the investigations by Kawai and Okamoto (1979) and D. Trenkler (1986) are extended to the most general situation of competing estimators.

How to Cite

Ihorst, G., & Trenkler, G. (1996). A general investigation of mean square error matrix superiority in linear regression. Statistica, 56(1), 15–25. https://doi.org/10.6092/issn.1973-2201/996