Bahadur Representation of Linear Kernel Quantile Estimator for Stationary Processes

被引：1
|
作者：
Huang Chu [1 ]
Zhang Li-Xin [1 ]
机构：
[1] Zhejiang Univ, Dept Math, Hangzhou 310003, Zhejiang, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2014年 / 43卷 / 22期
基金：
中国国家自然科学基金;
关键词：
S-mixing; Kernel quantile estimator; Bahadur representation; SAMPLE QUANTILES; SEQUENCES;
D O I：
10.1080/03610926.2012.736582
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 article, we discuss the method of linear kernel quantile estimator proposed by Parzen (1979). We establish a Bahadur representation in sense of almost surely convergence with the rate log-an under the case of S-mixing random variable sequence which was proposed by Berkes (2009). We also obtain the strong consistence of this estimator and its convergence rate.
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页码：4669 / 4678
页数：10
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