Empirical Likelihood-based Inferences in Varying Coefficient Models with Missing Data

作     者：Xiao-hui LIU 

作者机构：School of Statistics Jiangxi University of Finance and Economics Research Center of Applied Statistics Jiangxi University of Finance and Economics 

出 版 物：《Acta Mathematicae Applicatae Sinica》 (应用数学学报（英文版）)

年 卷 期：2015年第31卷第3期

页      面：823-840页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported in part by NSF of China(No.11461029) NSF of Jiangxi Province(No.20142BAB211014) YSFP of Jiangxi provincial education department(No.GJJ14350) 

主　　题：varying coefficient models missing at random empirical likelihood maximum empirical likelihood estimator 

摘      要：In this paper, we consider the empirical likelihood-based inferences for varying coefficient models Y = X^τα（U） ＋ ε when X are subject to missing at random. Based on the inverse probability-weighted idea, a class of empirical log-likelihood ratios, as well as two maximum empirical likelihood estimators, are developed for α（u）. The resulting statistics are shown to have standard chi-squared or normal distributions *** studies are also constructed to illustrate the finite sample properties of the proposed statistics.