Nonparametric quantile regression with missing data using local estimating equations

doi:10.1080/10485252.2022.2026353

	Nonparametric quantile regression with missing data using local estimating equations
	Wang, Chunyu 1; Tian, Maozai1,2,3,4 ; Tang, Man-Lai 5,6
	2022-01-02
发表期刊	JOURNAL OF NONPARAMETRIC STATISTICS
卷号	34 期号:1 页码:164-186
摘要	In this paper, we propose augmented inverse probability weighted (AIPW) local estimating equations in dealing with missing data in nonparametric quantile regression context. The missing mechanism here is missing at random. To avoid the problem of misspecification, we adopt nonparametric approach to estimate the propensity score and conditional expectations of estimating functions. The asymptotic properties of our proposed estimator are studied. Majorisation-minimisation algorithm is used to circumvent the nonsmoothness of check function at the origin. When it comes to the choice of bandwidth, the theoretical expression of local optimal bandwidth is derived based on asymptotic properties. Moreover, we apply smoothed bootstrap method to obtain the empirical mean square error and use cross-validation to determine the bandwidth in practice. Simulations are conducted to compare the performance of our proposed methods with other existing methods. Finally, we illustrate our methodology with an analysis of non-insulin-dependent diabetes mellitus data set.
关键词	Missing data augmented inverse probability weighted method local estimating equations nonparametric quantile regression
DOI	10.1080/10485252.2022.2026353
收录类别	SCIE
ISSN	1048-5252
语种	英语
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000748844600001
出版者	TAYLOR & FRANCIS LTD
原始文献类型	Article
EISSN	1029-0311
引用统计	被引频次[WOS]：0 [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/32023
专题	统计与数据科学学院
作者单位	1.Renmin Univ China, Ctr Appl Stat, Sch Stat, Beijing, Peoples R China; 2.Xinjiang Med Univ, Dept Med Engn & Technol, Urumqi, Peoples R China; 3.Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou, Peoples R China; 4.Xinjiang Univ Finance, Sch Stat & Informat, Urumqi, Peoples R China; 5.Brunel Univ London, Coll Engn Design Phys Sci, Dept Math, Uxbridge, Middx, England; 6.Hang Seng Univ Hong Kong, Dept Math Stat & Insurance, Siu Lek Yuen, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Wang, Chunyu,Tian, Maozai,Tang, Man-Lai. Nonparametric quantile regression with missing data using local estimating equations[J]. JOURNAL OF NONPARAMETRIC STATISTICS,2022,34(1):164-186.
APA	Wang, Chunyu,Tian, Maozai,&Tang, Man-Lai.(2022).Nonparametric quantile regression with missing data using local estimating equations.JOURNAL OF NONPARAMETRIC STATISTICS,34(1),164-186.
MLA	Wang, Chunyu,et al."Nonparametric quantile regression with missing data using local estimating equations".JOURNAL OF NONPARAMETRIC STATISTICS 34.1(2022):164-186.