The kurtosis coefficient and the linear discriminant function

被引：22

作者：

Peña, D ^{[1
]}

Prieto, FJ ^{[1
]}

机构：

[1] Univ Carlos III Madrid, Dept Stat & Econometr, E-28903 Getafe, Spain

来源：

STATISTICS & PROBABILITY LETTERS | 2000年 / 49卷 / 03期

关键词：

classification; kurtosis coefficient;

D O I：

10.1016/S0167-7152(00)00055-9

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this note we analyze the relationship between the direction obtained from the minimization of the kurtosis coefficient of the projections of a mixture of multivariate normal distributions and the linear discriminant function. We show that both directions are closely related and, in particular, that given two vector random variables having symmetric distributions with unknown means and the same covariance matrix, the direction which minimizes the kurtosis coefficient of the projection is the linear discriminant function. This result provides a way to compute the discriminant function between two normal populations in the case in which means and common covariance matrix are unknown. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：257 / 261

页数：5