Southwest Jiaotong University School of Mathematics

统计系

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美国佐治亚州立大学赵亦川教授的学术报告

来源:   作者:统计系     日期:2021-11-09 08:50:34   点击数:  

报告时间:20211113日上午9点(腾讯会议)


会议时间: 2021/11/13 08:30-10:30 (GMT+08:00)

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会议 ID763 835 613

会议密码:211109


报告三(北京时间20211113日上午9:00AM)

Title: Bayesian jackknife empirical likelihood

Abstract: Empirical likelihood is a very powerful nonparametric tool that does not require any distributional assumptions. Lazar (2003) showed that in Bayesian inference, if one replaces the usual likelihood with the empirical likelihood, then posterior inference is still valid when the functional of interest is a smooth function of the posterior mean. However, it is not clear whether similar conclusions can be obtained for parameters defined in terms of $U$-statistics. We propose the so-called Bayesian jackknife empirical likelihood, which replaces the likelihood component with the jackknife empirical likelihood. We show, both theoretically and empirically, the validity of the proposed method as a general tool for Bayesian inference. Empirical analysis shows that the small-sample performance of the proposed method is better than its frequentist counterpart. Analysis of a case-control study for pancreatic cancer is used to illustrate the new approach.

报告人简介:赵亦川教授目前任职于美国佐治亚州立大学,他的学术研究包括生存分析、经验似然方法、非参数统计、ROC曲线分析、生物信息学、蒙特卡洛方法和模糊系统的统计模型。赵教授在统计学和生物统计学研究领域发表了100多篇研究论文,合编了四本统计学和数据科学书籍,并应邀在国内外做了 200 多场学术报告. 2012年以来他组织了生物统计学和生物信息学系列研讨会,  作为组织委员会主席,在2016年他成功组织了在亚特兰大召开的大型国际学术会议。赵教授目前是若干统计学术期刊的编辑或编委会成员,也是美国统计学会(ASA)会士(Fellow)