Estimation of the probabilities of misclassification for a linear discriminant function in the univariate normal case

  • N. Sedransk
  • Masashi Okamoto


The probability of misclassification inherent in the use of a linear discriminant function is not necessarily known to the experimenter using such a function. Various estimators calculated from the sample used to generate the sample discriminant function have been proposed. The purpose of this paper is to evaluate and to compare several of these estimators by using unconditional mean square error as the criterion. Discussion is restricted to the case where each of the distributions is univariate normal with common variance.


Unbiased Estimator Normal Random Variable Multivariate Normal Distribution Classification Procedure Nonparametric Estimator 
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Copyright information

© Institute of Statistical Mathematics 1971

Authors and Affiliations

  • N. Sedransk
    • 1
    • 2
    • 3
  • Masashi Okamoto
    • 1
    • 2
    • 3
  1. 1.Iowa State UniversityUSA
  2. 2.University of WisconsinUSA
  3. 3.Osaka UniversityOsakaJapan

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