TY  - JOUR
AU  - El-Salam, Moawad El-Fallah Abd 
PY  - 2011
TI  - A Modification of the Ridge Type Regression Estimators
JF  - American Journal of Applied Sciences
VL  - 8
IS  - 1
DO  - 10.3844/ajassp.2011.97.102
UR  - https://thescipub.com/abstract/ajassp.2011.97.102
AB  - Problem statement: Many regression estimators have been used to remedy multicollinearity problem. The ridge estimator has been the most popular one. However, the obtained estimate is biased. Approach: In this stuyd, we introduce an alternative shrinkage estimator, called modified unbiased ridge (MUR) estimator for coping with multicollinearity problem. This estimator is obtained from Unbiased Ridge Regression (URR) in the same way that Ordinary Ridge Regression (ORR) is obtained from Ordinary Least Squares (OLS). Properties of MUR estimator are derived. Results: The empirical study indicated that the MUR estimator is more efficient and more reliable than other estimators based on Matrix Mean Squared Error (MMSE).Conclusion: In order to solve the multicollinearity problem, the MUR estimator was recommended.