Non-central limit theorems for random selections

被引：6
|
作者：
Berkes, Istvan [1 ]
Horvath, Lajos [2 ]
Schauer, Johannes [1 ]
机构：
[1] Graz Univ Technol, Inst Stat, A-8010 Graz, Austria
[2] Univ Utah, Dept Math, Salt Lake City, UT 84112 USA
来源：
PROBABILITY THEORY AND RELATED FIELDS | 2010年 / 147卷 / 3-4期
基金：
美国国家科学基金会;
关键词：
Random selection; Uniform asymptotic negligibility; Bootstrap; Functional limit theorems; Permutation statistics; BOOTSTRAP; CONVERGENCE;
D O I：
10.1007/s00440-009-0212-z
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：
Selection from finite sets is a basic procedure of statistics and the partial sum behavior of selected elements is completely known under the "uniform asymptotic negligibility" condition of central limit theory. The purpose of the present paper is to determine the asymptotic behavior of partial sums when the central limit theorem fails. As an application, we describe the limiting properties of permutation and bootstrap statistics in case of infinite variance.
引用
收藏
页码：449 / 479
页数：31
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