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.
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页码：529 / 536
页数：8
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