An empirical central limit theorem for dependent sequences

被引：33

作者：

Dedecker, Jerome

Prieur, Clementine

机构：

[1] Univ Paris 06, Lab Stat Theor & Appl, F-75013 Paris, France

[2] Inst Natl Sci Appl, LSP, GMM, F-31077 Toulouse 04, France

来源：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2007年 / 117卷 / 01期

关键词：

empirical distribution function; central limit theorem; dependence coefficients; mixing; dynamical systems;

D O I：

10.1016/j.spa.2006.06.003

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：

We prove a central limit theorem for the d-dimensional distribution function of a class of stationary sequences. The conditions are expressed in terms of some coefficients which measure the dependence between a given sigma-algebra and indicators of quadrants. These coefficients are weaker than the corresponding mixing coefficients, and can be computed in many situations. In particular, we show that they are well adapted to functions of mixing sequences, iterated random functions, and a class of dynamical systems. (C) 2006 Elsevier B.V.. All rights reserved.

引用

页码：121 / 142

页数：22

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