Applied Mathematics and Mechanics (English Edition) ›› 1994, Vol. 15 ›› Issue (4): 379-388.

• 论文 • 上一篇    下一篇

THE COMPRESSION LS ESTIMATE OF REGRESSION COEFFICIENT IN MULTIVARIATE LINEAR MODEL

陈世基1, 曾志斌2   

  1. 1. Dept. of Mathematics, Fujian Normal University, Fuzhou;
    2. Statistics Bureau of Fujian Province, Fuzhou
  • 收稿日期:1993-01-14 出版日期:1994-04-18 发布日期:1994-04-18
  • 基金资助:

    Project supported by the Natural Science Foundation of Fujian Province

THE COMPRESSION LS ESTIMATE OF REGRESSION COEFFICIENT IN MULTIVARIATE LINEAR MODEL

Chen Shi-ji1, Zeng Zhi-bin2   

  1. 1. Dept. of Mathematics, Fujian Normal University, Fuzhou;
    2. Statistics Bureau of Fujian Province, Fuzhou
  • Received:1993-01-14 Online:1994-04-18 Published:1994-04-18
  • Supported by:

    Project supported by the Natural Science Foundation of Fujian Province

摘要: In this paper, compression LS estimate B(k) of the regression coefficient B isconsidered when the design matrix present ill-condition in multivariate linear model.The MSE (mean square error)of the estimate β(k)=Vec(B(k))is less than theMSE of LS estimate β* of the regression coefficient β= Vec(B) by choosing the pa-rameter k. Admissibility , numerical stability and relative efficiency of β(k)are proved. The method of determining k value for practical use is also suggested.

关键词: compressible hyper-elastic material, cavitated bifurcation, catastrophe and concentration of stress, energy comparison, multivariate linear model, least square estimate, compression LS estimate, mean square error

Abstract: In this paper, compression LS estimate B(k) of the regression coefficient B isconsidered when the design matrix present ill-condition in multivariate linear model.The MSE (mean square error)of the estimate β(k)=Vec(B(k))is less than theMSE of LS estimate β* of the regression coefficient β= Vec(B) by choosing the pa-rameter k. Admissibility , numerical stability and relative efficiency of β(k)are proved. The method of determining k value for practical use is also suggested.

Key words: compressible hyper-elastic material, cavitated bifurcation, catastrophe and concentration of stress, energy comparison, multivariate linear model, least square estimate, compression LS estimate, mean square error

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