A CENTRAL-LIMIT-THEOREM FOR NONLINEAR FUNCTIONALS OF STATIONARY GAUSSIAN VECTOR PROCESSES

被引：0

作者：

DENARANJO, MVS ^{[1
]}

机构：

[1] UNIV LOS ANDES,FAC CIENCIAS,DEPT MATEMAT,MERIDA,VENEZUELA

来源：

STATISTICS & PROBABILITY LETTERS | 1995年 / 22卷 / 03期

关键词：

CENTRAL LIMIT THEOREM; STATIONARY GAUSSIAN VECTOR PROCESSES; HERMITE POLYNOMIALS; DIAGRAM FORMULA;

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：

Let X(n) = (X(n)1,...,X(n)d) be a stationary Gaussian vector process, such that the correlation matrix tends fast to 0. Suppose H is a d-dimensional function and define Z(N) (H) = (square-root N)1 SIMGA(j=1)N H(X(j)). It is shown that Z(N) (H) has a Guassian limiting distribution.

引用

页码：223 / 230

页数：8

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