New ridge parameters for ridge regression

AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS) estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation. In this article, a new method for estimating ridge parameters in both situations of ordinary ridge regression (ORR) and generalized ridge regression (GRR) is proposed. The simulation study evaluates the performance of the proposed estimator based on the mean squared error (MSE) criterion and indicates that under certain conditions the proposed estimators perform well compared to OLS and other well-known estimators reviewed in this article