The application of a new dependency measure to principal component analysis

被引：2

作者：

González-Barrios, JM ^{[1
]}

Ruiz-Velasco, S ^{[1
]}

机构：

[1] Univ Nacl Autonoma Mexico, IIMAS, Dept Probabil & Stat, Mexico City 01000, DF, Mexico

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2003年 / 32卷 / 03期

关键词：

principal component analysis; multivariate dependency measures; copulas;

D O I：

10.1081/SAC-120017867

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 article we study the relationship between principal component analysis and a multivariate dependency measure. It is shown, via simulated examples and real data, that the information provided by principal components is compatible with that obtained via the dependency measure S. Furthermore, we show that in some instances in which principal component analysis fails to give reasonable results due to nonlinearity among the random variables, the dependency statistic 8 still provides good results. Finally, we give some ideas about using the statistic 8 in order to reduce the dimensionality of a given data set.

引用

页码：899 / 921

页数：23