Influence functions and local influence in linear discriminant analysis

Yufen Huang, Tzu Ling Kao, Tai Ho Wang

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The perturbation theory provides a useful tool for the sensitivity analysis in linear discriminant analysis (LDA). Though some influence functions by single perturbation and local influence in LDA have been discussed in literature, we propose yet another influence function inspired by Critchley [1985. Influence in principal component analysis. Biometrika 72, 627-636], called the deleted empirical influence function, as an alternative approach for the influence analysis in LDA. It is well-known that single-perturbation diagnostics can suffer from the masking effect. Hence in this paper we also develop the pair-perturbation influence functions to detect the masked influential points. The comparisons between pair-perturbation influence functions and local influences in pairs in LDA are also investigated. Finally, two examples are provided to illustrate the results of these approaches.

Original languageEnglish
Pages (from-to)3844-3861
Number of pages18
JournalComputational Statistics and Data Analysis
Volume51
Issue number8
DOIs
Publication statusPublished - 2007 May 1

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Local Influence
Influence Function
Discriminant analysis
Discriminant Analysis
Perturbation
Influence Analysis
Masking
Principal component analysis
Principal Component Analysis
Perturbation Theory
Sensitivity analysis
Sensitivity Analysis
Diagnostics
Influence function
Alternatives

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

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Influence functions and local influence in linear discriminant analysis. / Huang, Yufen; Kao, Tzu Ling; Wang, Tai Ho.

In: Computational Statistics and Data Analysis, Vol. 51, No. 8, 01.05.2007, p. 3844-3861.

Research output: Contribution to journalArticle

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