Sequential change point detection in linear quantile regression models

被引：19

作者：

Zhou, Mi ^{[1
]}

Wang, Huixia Judy ^{[2
]}

Tang, Yanlin ^{[3
]}

机构：

[1] Fannie Mae, Washington, DC 20016 USA

[2] George Washington Univ, Dept Stat, Washington, DC 20052 USA

[3] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China

来源：

STATISTICS & PROBABILITY LETTERS | 2015年 / 100卷

基金：

美国国家科学基金会;

关键词：

Change point detection; Linear regression; Quantile regression; Sequential testing; Structural change; STRUCTURAL-CHANGE; PARAMETER;

D O I：

10.1016/j.spl.2015.01.031

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：

We develop a method for sequential detection of structural changes in linear quantile regression models. We establish the asymptotic properties of the proposed test statistic, and demonstrate the advantages of the proposed method over existing tests through simulation. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：98 / 103

页数：6

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