报告人: 梁汉营(同济大学)
报告时间: 5月8日 15:00-16:00
#腾讯会议:896-621-505
报告摘要: Based on empirical likelihood method, we investigate statistical inference in partially linear single-index quantile regression with high dimensional linear and single-index parameters when the observations are missing at random, which allows the response or covariates or response and covariates simultaneously missing. In particular, applying B-spline approximation to the unknown link function, we establish asymptotic normality of bias-corrected empirical likelihood ratio function and maximum empirical likelihood estimator of the parameters; variable selection are considered by using the SCAD penalty. Meanwhile, we propose a penalized empirical likelihood ratio statistic to test hypothesis, and prove its asymptotically chi-square distribution under the null hypothesis. Also, simulation study and a real data analysis are conducted to evaluate the performance of the proposed methods.
个人简介: 梁汉营,同济大学威尼斯人 教授,博士生导师。1997年博士毕业于武汉大学,1997-1999年在中国科技大学作博士后研究。主持过国家自然科学基金面上项目5项、国际合作项目1项和教育部项目2项,发表学术论文140余篇,曾获第十一届全国统计科研优秀成果奖二等奖、重庆市自然科学二等奖以及安徽省自然科学三等奖。现为中国现场统计研究会高维数据统计分会常务理事,中国现场统计研究会大数据统计分会常务理事。
研究兴趣:不完全数据的统计分析,分位数回归,高维数据分析,贝叶斯分析,经验似然,变点分析。
邀请人: 徐礼柏