A classification statistic from Anderson’s criterion in discrimination and its asymptotic distribution in the heteroscedastic normal model

A classification statistic from Anderson’s criterion in discrimination and its asymptotic distribution in the heteroscedastic normal model

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Article ID: iaor19971171
Country: United States
Volume: 16
Issue: 1/2
Start Page Number: 89
End Page Number: 107
Publication Date: Jan 1996
Journal: American Journal of Mathematical and Management Sciences
Authors:
Keywords: classification
Abstract:

T.W. Anderson introduced the likelihood ratio criterion which can be used in discrimination into one of two multivariate normal populations when the parameters of populations are estimated. This paper introduces a classification statistic based on Anderson’s likelihood ratio criterion. A deductive classification statistic is used in discrimination into one of several normal populations with unequal covariance matrices. The paper discusses its asymptotic distribution and its asymptotic behaviour for large samples. The asymptotic distribution is shown by the moment generating function, and some moments are given. An asymptotical mean bias and an asymptotic correct classifiction propbability give the asymptotic behaviour of the classification statistic.

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