ESTIMATION OF PRINCIPAL POINTS

被引：27

作者：

FLURY, BD

机构：

来源：

APPLIED STATISTICS-JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C | 1993年 / 42卷 / 01期

关键词：

ANTHROPOMETRIC DATA; ELLIPTIC DISTRIBUTION; K-MEANS CLUSTER ANALYSIS; LEAVE-ONE-OUT METHOD; MAXIMUM LIKELIHOOD ESTIMATION; NORMAL DISTRIBUTION; PRINCIPAL COMPONENTS;

D O I：

10.2307/2347416

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：

The k principal points of a p-variate random vector X are defined as those points xi1, . . ., xi(k) which minimize the expected squared distance between X and the nearest of the xi(j). This paper reviews some of the theory of principal points and redefines them in terms of self-consistent points. An anthropometrical problem which initiated the theoretical developments is described. Four methods of estimation, ranging from normal theory maximum likelihood to the usual k-means algorithm in cluster analysis, are introduced and applied to the example. Finally, a leave-one-out method is used to assess the performance of the four methods.

引用

页码：139 / 151

页数：13