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Selecting variables for discrimination when covariance matrices are unequal

Author

Listed:
  • Paranjpe, S. A.
  • Gore, A. P.

Abstract

Rao's (1973) test for additional information for discrimination between two multivariate normal populations is modified for the case of unequal covariance matrices. An application to the problem of discriminating between two geographic populations of tigers is provided.

Suggested Citation

  • Paranjpe, S. A. & Gore, A. P., 1994. "Selecting variables for discrimination when covariance matrices are unequal," Statistics & Probability Letters, Elsevier, vol. 21(5), pages 417-419, December.
    • Handle: RePEc:eee:stapro:v:21:y:1994:i:5:p:417-419
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    Citations

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    Cited by:

    1. Leiva, Ricardo, 2007. "Linear discrimination with equicorrelated training vectors," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 384-409, February.
    2. Tatjana Pavlenko & Anuradha Roy, 2013. "Supervised classifiers of ultra high-dimensional higher-order data with locally doubly exchangeable covariance structure," Working Papers 0185mss, College of Business, University of Texas at San Antonio.
    3. Leiva, Ricardo & Roy, Anuradha, 2012. "Linear discrimination for three-level multivariate data with a separable additive mean vector and a doubly exchangeable covariance structure," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1644-1661.

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