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Shrunken Estimators in Discriminant and Canonical Variate Analysis

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  • Norm A. Campbell

Abstract

Shrunken estimators in canonical variate analysis are shown to lead to improved stability of the resulting coefficients when the between‐groups sum of squares for a particular principal component defined by the within‐groups covariance or correlation matrix is small and the corresponding eigenvalue is also small.

Suggested Citation

  • Norm A. Campbell, 1980. "Shrunken Estimators in Discriminant and Canonical Variate Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 5-14, March.
    • Handle: RePEc:bla:jorssc:v:29:y:1980:i:1:p:5-14
    DOI: 10.2307/2346404
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    Cited by:

    1. Rasoul Lotfi & Davood Shahsavani & Mohammad Arashi, 2022. "Classification in High Dimension Using the Ledoit–Wolf Shrinkage Method," Mathematics, MDPI, vol. 10(21), pages 1-13, November.
    2. Shin, Hyejin, 2008. "An extension of Fisher's discriminant analysis for stochastic processes," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1191-1216, July.

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