题目：A simple and efficient profile likelihood for semiparametric exponential family
时间：2018年6月8日(周五)上午10:00-11:00
地点：闵行校区法商南楼135室
报告人：林路（山东大学金融研究院教授、副院长）
摘要：Semiparametric exponential family is an extension of the parametric exponential family to the case with a nonparametric base measure function. Such a distribution family has potential application in the cases of incomplete data, selection bias, heterogeneity and so on. However, the methodology for achieving the semiparametric efficiency has not been proposed in the existing literature. We propose a new profile likelihood to efficiently estimate both parameter and nonparametric function. Due to the use of the least favorable curve in the procedure of profile likelihood, the semiparametric efficiency is achieved successfully and the estimation bias is reduced significantly. Moreover, by making the most of the structure information of the semiparametric exponential family, the estimator of the least favorable curve has an explicit expression. It ensures that the newly proposed profile likelihood can be implemented and is computationally simple. Simulation studies can illustrate that our proposal is much better than the existing methodology for most cases under study, and is robust to the different model conditions.
报告人简介：林路，山东大学金融研究院教授、博士生导师、副院长；在南开大学获得博士学位后,先在南开大学任教，然后到山东大学任教至今；在高维统计、非参数和半参数统计以及金融统计等方面，取得许多重要的研究成果，在国际统计学和机器学习顶级刊物Annals of Statistics, Journal of Machine Learning Research和其它重要期刊发表研究论文90余篇；主持过多项国家自然科学基金课题、博士点专项基金课题、山东省自然科学基金重点项目等，获得过国家统计局颁发的统计科技进步二等奖，山东省优秀教学成果一等奖；是国家973项目、国家创新群体和教育部创新团队的核心成员，教育部应用统计专业硕士教育指导委员会成员，中国现场统计研究会生存分析分会副会长,山东省应用统计学会副会长，山东省政府参事。