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New shrinkage-type estimators in a linear regression model when multicollinearity is severe |
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| Authors: | Xu-Qing Liu Feng Gao Xun-Qing Wu |
| Affiliation: | 1. Faculty of Mathematics and Physics, Huaiyin Institute of Technology, Huai'an 223003, People's Republic of Chinaliuxuqing688@gmail.comliuxuqing688@163.com;4. Faculty of Mathematics and Physics, Huaiyin Institute of Technology, Huai'an 223003, People's Republic of China;5. Department of Basic Courses, Hunan Yiyang Vocational and Technical College, Hunan 413000, People's Republic of China |
| Abstract: | For the linear regression model y=Xβ+e with severe multicollinearity, we put forward three shrinkage-type estimators based on the ordinary least-squares estimator including two types of independent factor estimators and a seemingly convex combination. The simulation study shows that the new estimators are not good enough when multicollinearity is mild to moderate, but perform very well when multicollinearity is severe to very severe. |
| Keywords: | linear regression model ordinary least-squares estimator multicollinearity independent factor estimator combined independent factor estimator shrinkage-type estimator |