Performance of Some New Biasing Parameter Estimates of Kibria-Lukman Estimator in Linear Regression Model

الملخص

The objective of this study is to propose and examine some new estimators of estimating the biasing parameter in the estimator that was recently proposed and called the Kibria-Lukman (KL) estimator for combating the multicollinearity problem between the explanatory variables in the linear regression model based on the proposed estimation techniques of the biasing parameter in the ridge estimator because of the importance of the useful selection of the biasing parameter in this estimator. The simulation study and the real-life data have been performed to evaluate the performance of the proposed methods due to the mean squared error. Then, we determine the best-performed biasing parameter estimators.