Single-index composite quantile regression

被引：34
|
作者：
Jiang, Rong [1 ]
Zhou, Zhan-Gong [2 ]
Qian, Wei-Min [1 ]
Shao, Wen-Qiong [1 ]
机构：
[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
[2] Jiaxing Univ, Dept Stat, Jinxing 314001, Peoples R China
来源：
JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2012年 / 41卷 / 03期
关键词：
Asymptotic efficiency; Composite quantile regression; Single-index model; VARIABLE SELECTION; LEAST-SQUARES; COEFFICIENT; EFFICIENT; MODELS;
D O I：
10.1016/j.jkss.2011.11.001
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 paper, we extend the composite quantile regression (CQR) method to a single-index model. The unknown link function is estimated by local composite quantile regression and the parametric index is estimated through the linear composite quantile. It is shown that the proposed estimators are consistent and asymptotically normal. The simulation studies and real data applications are conducted to illustrate the finite sample performance of the proposed methods. (c) 2011 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：323 / 332
页数：10
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