REVSTAT-Statistical Journal, cilt.24, sa.1, ss.45-70, 2026 (SCI-Expanded, Scopus)
In linear regression models, researchers have developed new biased estimators to mitigate the effects of multicollinearity instead of using the Ordinary Least Squares (OLS) estimator, which is affected by multicollinearity. In this study, we define a general class of estimators called Ridge-type estimators (RTE). The superiority of RTE over other biased estimators is investigated under the matrix mean square error criterion. In addition, two separate Monte Carlo simulation studies are conducted to compare the performance of the considered biased estimators. A numerical example is given to demonstrate the superiority of the proposed estimator over other biased estimators.