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

被引：0
|
作者：
Geng Zhang
Shouquan Chen
机构：
[1] Southwest University,School of Mathematics and Statistics
来源：
Journal of the Korean Statistical Society | 2012年 / 41卷
关键词：
primary 60G15; secondary 60F05; 60G10; 60G70; Asymptotic distribution; Multivariate stationary Gaussian vector; Strongly dependent;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Let {Xn, n ≥ 1} be a sequence of d-dimensional stationary Gaussian vectors, and let Mn denote the maxima of {Xk, 1 ≤ k ≤ n{. Suppose that there are missing data in each component of Xk and let M̃n denote the maxima of the observed variables. In this paper, we study the asymptotic distribution of the random vector (M̃n, Mn) as the correlation and cross-correlation satisfy strongly dependent conditions.
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页码：529 / 536
页数：7
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