Prediction and discrimination with partial least squares method 最小2乗法による予測と判別

この論文をさがす

著者

    • 金, 鉉彬 キム, ヒョンビン

書誌事項

タイトル

Prediction and discrimination with partial least squares method

タイトル別名

最小2乗法による予測と判別

著者名

金, 鉉彬

著者別名

キム, ヒョンビン

学位授与大学

岡山大学

取得学位

博士 (学術)

学位授与番号

甲第1507号

学位授与年月日

1996-03-25

注記・抄録

博士論文

目次

  1. Contents / p1 (0003.jp2)
  2. 1. Introduction / p1 (0006.jp2)
  3. 2. Partial Least Squares(PLS)Method in Regression Analysis / p5 (0010.jp2)
  4. 2.1 Algorithm of Wold / p6 (0011.jp2)
  5. 2.2 Algorithm of Martens / p7 (0012.jp2)
  6. 2.3 Algorithm of Helland / p8 (0013.jp2)
  7. 3. Sensitivity Analysis in PLS Regression / p10 (0015.jp2)
  8. 3.1 Influence functions / p11 (0016.jp2)
  9. 3.2 Derivation of empirical influence function / p12 (0017.jp2)
  10. 3.3 Influence measures / p15 (0020.jp2)
  11. 3.4 Numerical example / p15 (0020.jp2)
  12. 3.5 Discussion / p18 (0023.jp2)
  13. 4. Comparison between PLS Regression and Principal Components Regression / p20 (0025.jp2)
  14. 4.1 Principal components regression / p20 (0025.jp2)
  15. 4.2 Design of simulation study / p21 (0026.jp2)
  16. 4.3 Result / p22 (0027.jp2)
  17. 4.4 Discussion / p28 (0033.jp2)
  18. 5. PLS Linear Discriminant Function / p30 (0035.jp2)
  19. 5.1 Linear discriminant function / p30 (0035.jp2)
  20. 5.2 Interpretation of the regression coefficient vector of PLS regression / p31 (0036.jp2)
  21. 5.3 PLS linear discriminant function / p32 (0037.jp2)
  22. 5.4 Choice of the number of components / p32 (0037.jp2)
  23. 5.5 Numerical examples / p34 (0039.jp2)
  24. 5.6 Discussion / p36 (0041.jp2)
  25. 6. Evaluation of PLS Linear Discriminant Function by Simulation Study / p38 (0043.jp2)
  26. 6.1 Design of simulation study / p38 (0043.jp2)
  27. 6.2 Comparison between PLS linear discriminant function and ordinary linear discriminant function / p39 (0044.jp2)
  28. 6.3 Comparison between two models for PLS linear discriminant function / p39 (0044.jp2)
  29. 6.4 Discussion / p41 (0046.jp2)
  30. 7. Application of PLS Linear Discriminant Function to Pattern Recognition Analysis / p44 (0049.jp2)
  31. 7.1 Writer identification / p44 (0049.jp2)
  32. 7.2 Arc pattern extraction / p45 (0050.jp2)
  33. 7.3 Applying PLS linear discriminant function / p48 (0053.jp2)
  34. 7.4 Discussion / p52 (0057.jp2)
  35. 8. Method of Generating Artificial Data with Preassigned Degree of Multicollinearity / p54 (0059.jp2)
  36. 8.1 Singular value decomposition / p54 (0059.jp2)
  37. 8.2 Proposed method for generating artificial data / p54 (0059.jp2)
  38. 8.3 Transformation of variables / p56 (0061.jp2)
  39. 8.4 Numerical examples / p58 (0063.jp2)
  40. 8.5 Discussion / p61 (0066.jp2)
  41. 9. Conclusion / p63 (0068.jp2)
  42. Appendix A / p65 (0070.jp2)
  43. Appendix B / p66 (0071.jp2)
  44. References / p72 (0077.jp2)
  45. Acknowledgement / p77 (0082.jp2)
1アクセス

各種コード

  • NII論文ID(NAID)
    500000130780
  • NII著者ID(NRID)
    • 8000000954516
  • DOI(NDL)
  • 本文言語コード
    • jpn
  • NDL書誌ID
    • 000000295094
  • データ提供元
    • 機関リポジトリ
    • NDL-OPAC
    • NDLデジタルコレクション
ページトップへ