Volume 24 Issue 5
May  1998
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Wang Huiwen, Yang Xianglong. Comparing Two Regression Methods Based on Different Principal Components[J]. Journal of Beijing University of Aeronautics and Astronautics, 1998, 24(5): 575-578. (in Chinese)
Citation: Wang Huiwen, Yang Xianglong. Comparing Two Regression Methods Based on Different Principal Components[J]. Journal of Beijing University of Aeronautics and Astronautics, 1998, 24(5): 575-578. (in Chinese)

Comparing Two Regression Methods Based on Different Principal Components

  • Received Date: 06 Mar 1997
  • Publish Date: 31 May 1998
  • This paper deals with the comparing two regression methods based on different principal components.The principal components acquired by principal component analysis are the best summery of the information in the independent variables' system,but generally they are short of the explanatory capability to the dependent variable.However the components acquired by using PLS regression can not only summarize the independent variables well,but also they have the best explanation to the dependent variable.Moreover,the interference from invalid information is eliminated at the same time.

     

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  • 1. Wold S,Albano C,Dunn III,et al.Pattern regression:Finding and using regularities in multivariate data.In:Martens J.Proc IUFOST Conf Food Research and Data.London:Analysis Applied Science Publication,1983 2. Tenenhaus M,Gauchi J P,Menardo C.Regression PLS et application.Revue de Statistiques Appliquees,1995,53(1):7~63 3. Marens H,Naes T.Multivariate calibration.New York:John Wiley & Sons,1989
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