Weighted composite quantile estimation and variable selection method for censored regression model

被引：38
|
作者：
Tang, Linjun [1 ]
Zhou, Zhangong [1 ]
Wu, Changchun [1 ]
机构：
[1] Jiaxing Univ, Dept Stat, Jiaxing 314001, Peoples R China
来源：
STATISTICS & PROBABILITY LETTERS | 2012年 / 82卷 / 03期
关键词：
Composite quantile regression; Inverse-censoring-probability; Variable selection; MEDIAN REGRESSION; SURVIVAL; LIKELIHOOD;
D O I：
10.1016/j.spl.2011.11.021
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：
This paper considers the weighted composite quantile (WCQ) regression for linear model with random censoring. The adaptive penalized procedure for variable selection in this model is proposed, and the consistency, asymptotic normality and oracle property of the resulting estimators are also derived. The simulation studies and the analysis of an acute myocardial infarction data set are conducted to illustrate the finite sample performance of the proposed method. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：653 / 663
页数：11
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