Volume 34 Issue 06
Jun.  2008
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Wang Huiwen, Wang Jie, Huang Haijunet al. Modeling strategy of principle component regression[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(06): 661-664. (in Chinese)
Citation: Wang Huiwen, Wang Jie, Huang Haijunet al. Modeling strategy of principle component regression[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(06): 661-664. (in Chinese)

Modeling strategy of principle component regression

  • Received Date: 15 May 2007
  • Publish Date: 30 Jun 2008
  • 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:①deriving all components and modeling with all these components; ②exclude all components which were not significant in t-test; ③modeling 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.

     

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