文章基本信息

标题：The Chi-plot and Its Asymptotic Confidence Interval for Analyzing Bivariate Dependence: An Application to the Average Intelligence and Atheism Rates across Nations Data
本地全文：下载
作者：Vitor A. A. Marchi ; Francisco A. R. Rojas ; Francisco Louzada 等
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2012
卷号：10
期号：4
页码：711-722
出版社：Tingmao Publish Company
摘要：Bivariate data analysis plays a key role in several areas wherethe variables of interest are obtained in a paired form, leading to the con-sideration of possible association measures between them. In most cases,it is common to use known statistics measures such as Pearson correlation,Kendall's and Spearman's coecients. However, these statistics measuresmay not represent the real correlation or structure of dependence betweenthe variables. Fisher and Switzer (1985) proposed a rank-based graphicaltool, the so called chi-plot, which, in conjunction with its Monte Carlo basedcondence interval can help detect the presence of association in a randomsample from a continuous bivariate distribution. In this article we constructthe asymptotic condence interval for the chi-plot. Via a Monte Carlo sim-ulation study we discovery the coverage probabilities of the asymptotic andthe Monte Carlo based condence intervals are similar. A immediate advan-tage of the asymptotic condence interval over the Monte Carlo based one isthat it is computationally less expensive providing choices of any condencelevel. Moreover, it can be implemented straightforwardly in the existingstatistical softwares. The chi-plot approach is illustrated in on the averageintelligence and atheism rates across nations data.
关键词：Analysis of dependence; chi-plot; condence intervals.