Empirical likelihood inference for estimating equation with missing data

查看全文 作　　者：WANG [1]XiuLi;CHEN [2]Fang;LIN [3]Lu

机构地区：[1]School of Mathematical Sciences, Shandong Normal University;[2]Department of Electronics Communication & Software Engineering, Nanfang College of Sun Yat-Sen University;[3]School of Mathematics, Shandong University

出　　处：《Science China Mathematics》索引2013年第56卷第6期,共13页

基　　金：supported by National Natural Science Foundation of China (Grant Nos.11171188, 11201499 and 10921101);Natural Science Foundation of Shandong Province (Grant Nos. ZR2010AZ001 and ZR2011AQ007);Shandong Provincial Scientific Research Reward Foundation for Excellent Young and MiddleAged Scientists (Grant No. BS2011SF006);K.C. Wong-HKBU Fellowship Program for Mainland Visiting Scholars 2010-11 摘　　要：In this article, empirical likelihood inference for estimating equation with missing data is considered. Based on the weighted-corrected estimating function, an empirical log-likelihood ratio is proved to be a standard chi-square distribution asymptotically under some suitable conditions. This result is different from those derived before. So it is convenient to construct confidence regions for the parameters of interest. We also prove that our proposed maximum empirical likelihood estimator θ is asymptotically normal and attains the semiparametric efficiency bound of missing data. Some simulations indicate that the proposed method performs the best. 关键词：估计函数似然推理方程经验似然比经验似然估计置信区间缺失数据施工方

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Empirical likelihood inference for estimating equation with missing data

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