报告题目：Empirical likelihood in semiparametric models (1)
报 告 人：薛留根 教授 北京工业大学
报告时间：2020年7月23日 9:00-10:00
报告地点：腾讯会议ID：691 621 889
或点击链接直接加入会议：
https://meeting.tencent.com/s/tN7KCVoSyzCa
校内联系人：程建华 chengjh@jlu.edu.cn
报告摘要：
In this talk, we discuss the empirical likelihood based inference problem in semiparametric models. Firstly, we investigate the empirical likelihood based inference for the parameters in a partially linear single-index model. we propose a bias correction method to achieve that the empirical likelihood ratio has standard chi-square limit. Secondly, we investigate the empirical likelihood-based inference for a varying coefficient model with longitudinal data. we propose three empirical likelihood ratios: the naive empirical likelihood ratio, the mean-corrected empirical likelihood ratio and the residual-adjusted empirical likelihood ratio, and show that these ratios have chi-square limits. In addition, when some components are of particular interest, we suggest the mean-corrected and residual-adjusted partial empirical likelihood ratios for the construction of the confidence regions/intervals. A simulation study is undertaken to compare the empirical likelihood and the normal approximation methods in terms of coverage accuracies and average areas/widths of confidence regions/intervals. An example in epidemiology is used for illustration.
报告人简介：
薛留根，北京工业大学教授，博士生导师。主要学术兼职：中国现场统计研究会理事及生存分析分会副理事长等。主要研究兴趣为非参数与半参数模型的统计推断、复杂数据分析与建模、经验似然等。主持国家和省部级科研项目15项。出版著作8部，其中3部专著。在《Journal of the American Statistical Association》、《Journal of the Royal Statistical Society，Series B》、《The Annals of Statistics》、《Biometrika》等学术期刊上发表学术论文240余篇，其中2篇为高被引论文。以第一完成人获教育部自然科学二等奖1项，获全国统计科学研究优秀成果一等奖1项。已招收研究生65人，其中博士研究生20人，硕士研究生45人；指导的研究生中1人获北京市优秀博士学位论文以及全国优秀博士学位论文提名奖，1人获全国统计科学研究优秀成果博士学位论文二等奖。
