Graphical assessment of dependence: Is a picture worth 100 tests?

被引：101

作者：

Fisher, NI

Switzer, P

机构：

[1] Univ Sydney, Sch Math, Sydney, NSW 2006, Australia

[2] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

来源：

AMERICAN STATISTICIAN | 2001年 / 55卷 / 03期

关键词：

chi-plot; copula; nonparametric association; rank tests of independence;

D O I：

10.1198/000313001317098248

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：

Nonparametric tests of association have been around for a long time, and new ones continue to be proposed to cope with specific forms of association. However, graphs have the potential to assess a far richer class of bivariate dependence structures than any collection of tests. This article describes how chi-plots, used in conjunction with the usual scatterplot, provides a useful practical tool in this regard.

引用

页码：233 / 239

页数：7

共 6 条

[1] GRAPHICAL METHODS IN NONPARAMETRIC STATISTICS - A REVIEW AND ANNOTATED-BIBLIOGRAPHY [J].