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Linear Discrimination with Adaptive Ridge Classification Rules

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  • Loh, Wei-Liem

Abstract

This article considers the use of adaptive ridge classification rules for classifying an observation as coming from one of two multivariate normal distributionsN([mu](1), [Sigma]) andN([mu](2), [Sigma]). In particular, the asymptotic expected error rates for a general class of these rules are obtained and are compared with that of the usual linear discriminant rule.

Suggested Citation

  • Loh, Wei-Liem, 1997. "Linear Discrimination with Adaptive Ridge Classification Rules," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 169-180, August.
    • Handle: RePEc:eee:jmvana:v:62:y:1997:i:2:p:169-180
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    References listed on IDEAS

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    1. T. Anderson, 1951. "Classification by multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 16(1), pages 31-50, March.
    2. Loh, W. L., 1995. "On Linear Discriminant Analysis with Adaptive Ridge Classification Rules," Journal of Multivariate Analysis, Elsevier, vol. 53(2), pages 264-278, May.
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    Cited by:

    1. Raudys, Sarunas & Young, Dean M., 2004. "Results in statistical discriminant analysis: a review of the former Soviet Union literature," Journal of Multivariate Analysis, Elsevier, vol. 89(1), pages 1-35, April.
    2. Kubokawa, Tatsuya & Srivastava, Muni S., 2008. "Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1906-1928, October.

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