报告题目:Efficient Estimation for Varying-Coefficient Mixed Effects Models with Functional Response Data

报告人：北京工业大学 薛留根教授

报告时间：2021年5月9日 15:00-18:00

报告地点：数学与统计学院310会议室

报告内容摘要：In this talk, we focus on the estimation of varying-coefficient mixed effects models for longitudinal and sparse functional response data, by using the generalized least squares method coupling a modified local kernel smoothing technique. This approach provides a useful framework that simultaneously takes into account the within-subject covariance and all observation information in the estimation to improve efficiency. We establish both uniform consistency and pointwise asymptotic normality for the proposed estimators of varying-coefficient functions. Numerical studies are carried out to illustrate the finite sample performance of the proposed procedure. An application to the white matter tract dataset obtained from Alzheimer’s Disease Neuroimaging Initiative study is also provided.

报告人简介：北京工业大学应用数理学院教授，统计学博士生导师。主要学术兼职有：中国现场统计研究会理事及生存分析分会副理事长，全国工业统计学教学研究会理事等。主持完成和在研的国家和省部级科研项目15项。出版著作8部（独著6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》等国内外学术期刊上发表学术论文200余篇，其中2篇属高被引论文。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奖一等奖和二等奖各1项。