Studying the Performance of Two Ridge Estimators Using Least Absolute Deviation

Abstract

Multicollinearity is one of the essential and implicit problems in the regression analysis due to its influence on the model estimators. The problem is the independent variables are highly correlated, and the regression results are unclear. The purpose of this paper is to solve this problem using one of the solutions available, one of these solutions is the ridge regression of Least Absolute Deviation (LAD) estimators through adding a suggested ridge parameter as modify ridge parameter of (Hoerl et al. (1975)) say (K ̂_HKB). A simulation study was performed to compare (K ̂_HKB) and the suggested ridge parameter using Mean Square Error (MSE) to determine the best one.