报告人：胡涛

报告时间：2024年6月22日 14:00—16:00

报告地点：北区4号教学楼208报告厅

报告题目：Simultaneous variable selection and estimation in semiparametric regression of mixed panel count data

报告摘要：Mixed panel count data represent a common complex data structure in longitudinal survey studies. A major challenge in analyzing such data is variable selection and estimation while efficiently incorporating both the panel count and panel binary data components. Analyses in the medical literature have often ignored the panel binary component and treated it as missing with the unknown panel counts, while obviously such a simplification does not effectively utilize the original data information. In this research, we put forward a penalized likelihood variable selection and estimation procedure under the proportional mean model. A computationally efficient EM algorithm is developed that ensures sparse estimation for variable selection, and the resulting estimator is shown to have the desirable oracle property. Simulation studies assessed and confirmed the good finite-sample properties of the proposed method, and the method is applied to analyze a motivating dataset from the Health and Retirement Study.

专家简介：胡涛，首都师范大学数学科学学院教授，博士生导师。研究方向：生物统计、应用统计。在国内外学术刊物Journal of the American Statistical Association、Biometrika、Bioinformatics、Biometrics、Renewable Energy和中国科学：数学等上发表学术论文多篇。主持北京高校卓越青年科学家计划项目、国家自然科学基金面上项目、北京市自然科学基金重点研究专题等多个课题。