Empirical Likelihood for Composite Quantile Regression Models with Missing Response Data

被引:0
作者
Luo, Shuanghua [1 ,2 ]
Zheng, Yu [1 ]
Zhang, Cheng-yi [3 ,4 ]
机构
[1] Xian Polytech Univ, Sch Sci, Xian 710048, Peoples R China
[2] Xian Int Sci & Technol, Cooperat Base Big Data Anal & Algorithms, Xian 710048, Peoples R China
[3] Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710061, Peoples R China
[4] Xi An Jiao Tong Univ, Philosophy & Social Sci Lab, Minist Educ China, Syst Behav & Management Lab, Xian 710061, Peoples R China
来源
SYMMETRY-BASEL | 2024年 / 16卷 / 10期
关键词
empirical likelihood; composite quantile regression; missing response data; confidence interval; INFERENCE;
D O I
10.3390/sym16101314
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Under the assumption of missing response data, empirical likelihood inference is studied via composite quantile regression. Firstly, three empirical likelihood ratios of composite quantile regression are given and proved to be asymptotically chi 2. Secondly, without an estimation of the asymptotic covariance, confidence intervals are constructed for the regression coefficients. Thirdly, three estimators are presented for the regression parameters to obtain its asymptotic distribution. The finite sample performance is assessed through simulation studies, and the symmetry confidence intervals of the parametric are constructed. Finally, the effectiveness of the proposed methods is illustrated by analyzing a real-world data set.
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页数:16
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