A CENTRAL LIMIT THEOREM FOR MULTIVARIATE STRONGLY MIXING RANDOM FIELDS

被引：0

作者：

Tone, Cristina ^{[1
]}

机构：

[1] Univ Louisville, Dept Math, Louisville, KY 40292 USA

来源：

PROBABILITY AND MATHEMATICAL STATISTICS-POLAND | 2010年 / 30卷 / 02期

关键词：

Central limit theorem; alpha-mixing; random field of random vectors;

D O I：

暂无

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：

In this paper we extend a theorem of Bradley under interlaced mixing and strong mixing conditions. More precisely, we study the asymptotic normality of the normalized partial sum of an alpha-mixing strictly stationary random field of random vectors, in the presence of another dependence assumption.

引用

页码：215 / 222

页数：8

共 7 条

[1]

[Anonymous], PROBAB MATH STAT

[2]

[Anonymous], 1999, CONVERGE PROBAB MEAS

[3]

Billingsley P., 1995, Probability and Measure

[4]

Bradley R. C., 2007, INTRO STRONG MIXING, V3

[5]

Bradley R.C., 2007, Introduction to Strong Mixing Conditions, V1

[6] On the asymptotic normality of sequences of weak dependent random variables [J].

Peligrad, M .

JOURNAL OF THEORETICAL PROBABILITY, 1996, 9 (03) :703-715

[7] Maximal inequalities and an invariance principle for a class of weakly dependent random variables [J].

Utev, S ;

Peligrad, M .

JOURNAL OF THEORETICAL PROBABILITY, 2003, 16 (01) :101-115

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