吉林大学学报（理学版）2016，Vol.54Issue(5)：1008-1016,9.DOI:10.13413/j.cnki.jdxblxb.2016.05.14
缺失数据下基于经验似然的加权复合分位数回归推断
Estimation of Weighted Composite Quantile Regression with Missing Covariates Based on Empirical Likelihood
摘要
Abstract
We proposed a weighted composite quantile regression method based on empirical likelihood in linear model with some covariates missing at random,and proved the large sample properties of the proposed method under the missing at random mechanism.The results show that the proposed method is computationally simple and the estimation efficiency of the regression parameters is higher than that of the inverse probability weighted method.关键词
线性模型/随机缺失/经验似然/复合分位数回归/逆概率加权Key words
linear model/missing at random/empirical likelihood/composite quantile regression/inverse probability weighting分类
数理科学引用本文复制引用
袁晓惠,赵雪冬..缺失数据下基于经验似然的加权复合分位数回归推断[J].吉林大学学报（理学版）,2016,54(5):1008-1016,9.基金项目
国家自然科学基金(批准号:11401048 （）
11301037)和吉林省科技厅青年科研基金(批准号:20150520055JH （）
20150520054JH) （）
