CROSS-VALIDATORY CHOICE FOR THE NUMBER OF PRINCIPAL COMPONENTS IN PRINCIPAL COMPONENT REGRESSION

Abstract

We propose a cross-validatory method to choose the number of principal components in principal component regression based on the predicted error sum of squares. In the process of computation, we propose to use an approximation formula using a linear approximation based on the perturbation expansion. A numerical example is given to show the validity of the proposed method.

Journal

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

Journal of the Japanese Society of Computational Statistics 9(1), 53-59, 1996-12  [Table of Contents]

Japanese Society of Computational Statistics

References:  7

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Codes

  • NII Article ID (NAID) :
    110001235626
  • NII NACSIS-CAT ID (NCID) :
    AA10823693
  • Text Lang :
    ENG
  • Article Type :
    ART
  • ISSN :
    09152350
  • Databases :
    CJP  NII-ELS 

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