Abstract
Ridge regression is used to circumvent the effect of multicollinearity. Ridge parameter plays an important role in reducing the variance of ridge estimators. In this paper, we consider some existing estimators and propose some new ridge regression estimators for linear regression models. The performance of estimators is evaluated through a Monte Carlo simulation study. Based on mean square error criterion, our proposed estimators show some better performance as compared to other considered ridge estimators. An application is also given to illustrate the simulation results.
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