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研究生:郭玫伶
研究生(外文):Mei-Ling Kuo
論文名稱(外文):Pair-Perturbations on Influence Functions and Local Influence in PCA
指導教授:黃郁芬黃郁芬引用關係
指導教授(外文):Yu-Fen Huang
學位類別:碩士
校院名稱:國立中正大學
系所名稱:數理統計研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:33
外文關鍵詞:influence functionlocal influenceprincipal component analysisperturbation
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The perturbation theory of eigenvalue problems provides a useful mathematical tool in sensitive analysis for Principal Component Analysis ( PCA ). Single-perturbation on influence functions and local influence in PCA has been discussed by many authors. However, it is well known that single-perturbation diagnostics can suffer from a form of masking. Thus, pair-perturbations on influence functions for eigenvalues and eigenvectors need to be developed to detect the masked influential points in PCA. In this thesis, we derive the influence functions and local influence of
pair-perturbations,and examine relationships and make comparisons
among these influence functions and local influence. An example to these approaches to illustrate the results is also provided.
Abstract
1 Introduction................................................1
2 Pair-Perturbations on Influence Functions...................2
2.1 Empirical Influence Function............................4
2.2 Deleted Empirical Influence Function....................5
2.3 Sample Influence Function...............................6
3 Local Influence Function....................................7
4 Example.....................................................10
5 Conclusion and Discussion...................................15
References....................................................20
Appendix......................................................20
1 Critchley, F.(1985). Influence in principal component analysis. Biometrika 72, 627-636.
2 Cook, R. D.(1986). Assessment of local influence. J. R. Statist. Soc. B 48, 133-169.
3 Cook, R. D. & Weisberg, S.(1982). Residuals and influence in Regression. New York: Chapman & Hall.
4 Dunteman, G. H.(1989). Principal Components Analysis.
Sage University Paper.
5 Jolliffe, I. T.(1986). Principal Component Analysis. Springer-Verlag.
6 Johnson, R. A. & Wichern, D. W.(1998). Applied Multivariate Statistical Analysis, fourth ed. Prentice-Hall.
7 Kendall, M. G.(1975). Multivariate Analysis. London: Griffin.
8 Shi, L.(1997). Local influence in principal component analysis.
Biometrika 84, 175-186.
9 Tanaka, Y.(1988). Sensitivity analysis in principal component analysis: influence on the subspace spanned by principal components. Commun. Statist. A 17, 3157-3175.
10 Tanaka, Y. & Zhang, F.(1999). R-mode and Q-mode influence analyses in statistical modelling: relationship between influence function approach and local influence approach. Computational Statistics and Data Analysis 32, 197-218.
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