Moments and cumulants of the extremes of a sample from a uniform distribution

被引：0

作者：

Withers, Christopher S. ^{[1
]}

Nadarajah, Saralees ^{[2
]}

机构：

[1] Ind Res Ltd, Lower Hutt, New Zealand

[2] Univ Manchester, Manchester M13 9PL, Lancs, England

来源：

STATISTICS & PROBABILITY LETTERS | 2019年 / 145卷

关键词：

Edgeworth expansion; Order; Unbiasedness; MINIMA; MAXIMA;

D O I：

10.1016/j.spl.2018.10.006

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：

We give expansions in inverse powers of the sample size n for the joint moments and cumulants of the extremes when sampling from a uniform distribution. Estimates of low bias are given for smooth functions of the end points and their performance illustrated by simulations. Some extensions are given for general bivariate extreme estimates. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：238 / 247

页数：10

共 11 条

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