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June, 1962 Classification into two Multivariate Normal Distributions with Different Covariance Matrices
T. W. Anderson, R. R. Bahadur
Ann. Math. Statist. 33(2): 420-431 (June, 1962). DOI: 10.1214/aoms/1177704568


Linear procedures for classifying an observation as coming from one of two multivariate normal distributions are studied in the case that the two distributions differ both in mean vectors and covariance matrices. We find the class of admissible linear procedures, which is the minimal complete class of linear procedures. It is shown how to construct the linear procedure which minimizes one probability of misclassification given the other and how to obtain the minimax linear procedure; Bayes linear procedures are also discussed.


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T. W. Anderson. R. R. Bahadur. "Classification into two Multivariate Normal Distributions with Different Covariance Matrices." Ann. Math. Statist. 33 (2) 420 - 431, June, 1962.


Published: June, 1962
First available in Project Euclid: 27 April 2007

zbMATH: 0113.13702
MathSciNet: MR141198
Digital Object Identifier: 10.1214/aoms/1177704568

Rights: Copyright © 1962 Institute of Mathematical Statistics

Vol.33 • No. 2 • June, 1962
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