Performance of a New Ridge Regression Estimator

Abstract

Ridge regression estimator has been introduced as an alternative to the ordinary least squares estimator (OLS) in the presence of multicollinearity. Several studies concerning ridge regression have dealt with the choice of the ridge parameter. Many algorithms for the ridge parameter have been proposed in the statistical literature. In this article, a new method for estimating ridge parameter is proposed. A simulation study has been made to evaluate the performance of the proposed estimator based on the mean squared error (MSE) criterion. The evaluation has been done by comparing the MSEs of the proposed estimator with other well-known estimators. In the presence of multicollinearity, the simulation study indicates that under certain conditions the proposed estimator performs better than other estimators.