SECOND ORDER LOCAL INFLUENCE IN LINEAR DISCRIMINANT ANALYSIS

    • Jung Kang-Mo
    • Department of Computer Science and Statistics, Kunsan National University
    • Kim Byung Chun
    • Department of Industrial Management, Korea Advanced Institute of Science and Technology

Abstract

We adapt the local influence method to linear discriminant analysis for the purpose of investigating the influence of observations. A simultaneous perturbation on all observations coming from two populations is considered. We study the curvatures and the associated direction vectors of the surface formed by the perturbed maximum likelihood estimators of parameters of interest, in addition to the direction vector of the maximum slope. We show that the influence function method gives essentially the same information as the direction vector of the maximum slope. A numerical example illustrates that the local influence method gives valuable information about influential observations and outliers, even when the influence function method and the case deletion method are not adequate.

Journal

Journal of the Japanese Society of Computational Statistics   [List of Volumes]

Journal of the Japanese Society of Computational Statistics 10(1), 1-11, 1997-12  [Table of Contents]

Japanese Society of Computational Statistics

References:  9

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Codes

  • NII Article ID (NAID) :
    110001235552
  • NII NACSIS-CAT ID (NCID) :
    AA10823693
  • Text Lang :
    ENG
  • Article Type :
    ART
  • ISSN :
    09152350
  • Databases :
    CJP  NII-ELS 

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