Weak invariance principles for sums of dependent random functions

被引：44

作者：

Berkes, Istvan ^{[1
]}

Horvath, Lajos ^{[2
]}

Rice, Gregory ^{[2
]}

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：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2013年 / 123卷 / 02期

基金：

美国国家科学基金会; 奥地利科学基金会;

关键词：

Variables in Hilbert spaces; m-approximability; Weak convergence; VALUED RANDOM-VARIABLES; CENTRAL-LIMIT-THEOREM; STATIONARY-PROCESSES; MOMENT; SPACE;

D O I：

10.1016/j.spa.2012.10.003

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：

Motivated by problems in functional data analysis, in this paper we prove the weak convergence of normalized partial sums of dependent random functions exhibiting a Bernoulli shift structure. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：385 / 403

页数：19

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