Limit distribution of maxima of strongly dependent Gaussian vector sequences under complete and incomplete samples

被引：0

作者：

Zhang, Geng ^{[1
]}

Chen, Shouquan ^{[1
]}

机构：

[1] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China

来源：

JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2012年 / 41卷 / 04期

关键词：

Asymptotic distribution; Multivariate stationary Gaussian vector; Strongly dependent; STATIONARY-SEQUENCES;

D O I：

10.1016/j.jkss.2012.03.003

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：

Let {X-n, n >= 1} be a sequence of d-dimensional stationary Gaussian vectors, and let M-n denote the maxima of {X-k, 1 <= k <= n}. Suppose that there are missing data in each component of X-k and let (M) over tilde (n) denote the maxima of the observed variables. In this paper, we study the asymptotic distribution of the random vector ((M) over tilde (n), M-n) as the correlation and cross-correlation satisfy strongly dependent conditions. (C) 2012 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

引用

页码：529 / 536

页数：8

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