Empirical likelihood in single-index quantile regression with high dimensional and missing

讲座名称: Empirical likelihood in single-index quantile regression with high dimensional and missing
讲座时间: 2024-01-05
讲座人: 梁汉营
形式: 线下
校区: 兴庆校区
实践学分:
讲座内容:

报告人:梁汉营教授

报告时间:2024-1-5(星期五)10:00-11:00

报告地点:数学楼2-2

报告题目:Empirical likelihood in single-index quantile regression with high dimensional and missing observations

 

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,同济大学数学科学学院教授,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,曾获得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。主要的研究兴趣:不完全数据的统计分析,经验似然,分位数回归,变点分析,高维数据分析,贝叶斯分析。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。

 

信息来源:http://math.xjtu.edu.cn/info/1089/12923.htm

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