The Performance of some biased estimators with different biased parameter in Linear Regression Model

Abstract

To circumvent the problem of multicollinearity, biased estimation method has been suggested to improve the precision of estimators. In this paper, we study types of biased estimators that can help to reduce the effect of multicollinearity on estimation. A simulation study is carried out to study the relative effectiveness of certain types of biased estimators in comparison to some  proposed estimated ridge parameter (k) that have been shown in the literature . Moreover, a real data set has been considered to support the simulation results based on the estimated mean square error criterion.