Goodness-of-fit tests for the Cauchy distribution

被引：5

作者：

Onen, BH ^{[1
]}

Dietz, DC ^{[1
]}

Yen, VC ^{[1
]}

Moore, AH ^{[1
]}

机构：

[1] USAF, Inst Technol, AFIT EN, Wright Patterson AFB, OH 45433 USA

来源：

COMPUTATIONAL STATISTICS | 2001年 / 16卷 / 01期

关键词：

Cauchy distribution; goodness-of-fit; Monte Carlo; Kolmogorov-Smirnov test; Kuiper test;

D O I：

10.1007/s001800100053

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：

This article presents several modified goodness-of-fit tests for the Cauchy distribution with unknown location and scale parameters. Monte Carlo studies are performed to calculate critical values for several tests based on the empirical distribution function. Power studies suggest that the modified Kuiper (V) test is the most powerful standard test against most alternate distributions over a full range of sample sizes. A reflection technique is also employed which yields substantial improvement in the power of this test against symmetric distributions.

引用

页码：97 / 107

页数：11

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