Testing the variance of symmetric heavy-tailed distributions

被引：3

作者：

Lee, SJ ^{[1
]}

Sa, P ^{[1
]}

机构：

[1] UNIV N FLORIDA,DEPT MATH & STAT,JACKSONVILLE,FL 32224

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 1996年 / 56卷 / 01期

关键词：

Edgeworth expansion; type I error rate; symmetric heavy-tailed distribution; positive coefficient of kurtosis;

D O I：

10.1080/00949659608811779

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Currently, the most commonly used test of a single variance is the chi-square test when the population is normal. In this article, a new test procedure is proposed for the upper-tailed test for the variance of any symmetric heavy-tailed populations. Edgeworth expansion is used to derive the new test statistic. A Monte Carlo study investigates the properties of the new procedure for a variety of symmetric heavy-tailed distributions. It is shown that the new test yields controlled type I error rates as well as good power performances when the sample size is moderate or large.

引用

页码：39 / 52

页数：14

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