Variable selection for ultra-high dimensional quantile regression with missing data and measurement error

doi:10.1177/0962280220941533

	Variable selection for ultra-high dimensional quantile regression with missing data and measurement error
	Bai, Yongxin 1; Tian, Maozai1,2,3 ; Tang, Man-Lai 4,5; Lee, Wing-Yan 4
	2021-01
发表期刊	STATISTICAL METHODS IN MEDICAL RESEARCH
卷号	30 期号:1 页码:129-150
摘要	In this paper, we consider variable selection for ultra-high dimensional quantile regression model with missing data and measurement errors in covariates. Specifically, we correct the bias in the loss function caused by measurement error by applying the orthogonal quantile regression approach and remove the bias caused by missing data using the inverse probability weighting. A nonconvex Atan penalized estimation method is proposed for simultaneous variable selection and estimation. With the proper choice of the regularization parameter and under some relaxed conditions, we show that the proposed estimate enjoys the oracle properties. The choice of smoothing parameters is also discussed. The performance of the proposed variable selection procedure is assessed by Monte Carlo simulation studies. We further demonstrate the proposed procedure with a breast cancer data set.
关键词	Quantile regression Atan penalty measurement error missing data HBIC criterion
DOI	10.1177/0962280220941533
收录类别	SCOPUS ; SCIE
ISSN	0962-2802
语种	英语
WOS研究方向	Health Care Sciences & Services ; Mathematical & Computational Biology ; Medical Informatics ; Mathematics
WOS类目	Health Care Sciences & Services ; Mathematical & Computational Biology ; Medical Informatics ; Statistics & Probability
WOS记录号	WOS:000556308900001
出版者	SAGE PUBLICATIONS LTD
原始文献类型	Article
EISSN	1477-0334
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/21308
专题	统计与数据科学学院
通讯作者	Tang, Man-Lai
作者单位	1.Renmin Univ China, Ctr Appl Stat, Sch Stat, Beijing 100872, Peoples R China; 2.Xinjiang Univ Finance & Econ, Sch Stat & Informat, Urumqi, Peoples R China; 3.Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou, Peoples R China; 4.Hang Seng Univ Hong Kong, Dept Math Stat & Insurance, Siu Lek Yuen, Peoples R China; 5.Hang Seng Univ Hong Kong, Big Data Intelligence Ctr, Siu Lek Yuen, Peoples R China
推荐引用方式 GB/T 7714	Bai, Yongxin,Tian, Maozai,Tang, Man-Lai,et al. Variable selection for ultra-high dimensional quantile regression with missing data and measurement error[J]. STATISTICAL METHODS IN MEDICAL RESEARCH,2021,30(1):129-150.
APA	Bai, Yongxin,Tian, Maozai,Tang, Man-Lai,&Lee, Wing-Yan.(2021).Variable selection for ultra-high dimensional quantile regression with missing data and measurement error.STATISTICAL METHODS IN MEDICAL RESEARCH,30(1),129-150.
MLA	Bai, Yongxin,et al."Variable selection for ultra-high dimensional quantile regression with missing data and measurement error".STATISTICAL METHODS IN MEDICAL RESEARCH 30.1(2021):129-150.