Using improved estimation strategies to combat multicollinearity

Abstract

In this approach, some generalized ridge estimators are defined based on shrinkage foundation. Completely under the suspicion that some sub-space restrictions may occur, we present the estimators of the regression coefficients combining the idea of preliminary test estimator and Stein-rule estimator with the ridge regression methodology for normal models. Their exact risk expressions in addition to biases are derived and the regions of optimality of the estimators are exactly determined along with some numerical analysis. In this regard, the ridge parameter is determined in different disciplines.