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Modeling strategy of principle component regression
Wang Huiwen, Wang Jie, Huang Haijun*
School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

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Abstract�� When the mechanism and the reason of failure of the classical principal components regression were analyzed, a new strategy of PCR modeling was presented as:��deriving all components and modeling with all these components; ��exclude all components which were not significant in ��t��-test; ��modeling with the components which were significant in ��t��-test. Proved the regression coefficient and the ��t��-test value of any principal component were unrelated to the other principal components. It was insured that, when applying backward-delete variables law, all the variables which were not significant in ��t��-test test could be deleted together at the same time. It was not necessary to delete them gradually. A simulation study was given to prove the validity of the strategy. The research indicates that the suggested strategy can effectively derive components which are explainable to dependent variables. Modeling under the condition of multicollinearity is enabled, and all the independent variables can be included. The process of suggested variables selection method is simple, and the accumulated error is smaller than that of partial least-squares regression.
Keywords�� regression analysis   principal component analysis   components   selection     
Received 2007-05-15;
Fund:

������Ȼ��ѧ����������Ŀ(70371007,70521001,70531010); ��������Ȼ��ѧ����������Ŀ(9052006)

About author: ������(1957-),Ů,����������,����,wanghw@vip.sina.com.
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������, ����, �ƺ���.���ɷֻع�Ľ�ģ�����о�[J]  �������պ����ѧѧ��, 2008,V34(06): 661-664
Wang Huiwen, Wang Jie, Huang Haijun.Modeling strategy of principle component regression[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2008,V34(06): 661-664
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