报告题目：Integrated Subgroup Identification from Multi-source Data

报告人：张伟平 教授

单位：中国科学技术大学

报告时间：2023 年10月21日（星期六）14:30-18:00

报告地点：翡翠湖校区科教楼A座1106

报告摘要：

Subgroup identification is crucial in dealing with the heterogeneous population and has wide applications in various areas, such as clinical trials and market segmentation. With the prevalence of multi-source data, there is a practical need to identify subgroups based on multi-source data. This paper proposes a working-independence pseudo-loglikelihood and integrates the parameters of each source into a pairwise fusion penalty for simultaneous parameter estimation and subgroup identification. We derive an alternating direction method of multipliers (ADMM) algorithm for its implementation. Furthermore, the weak oracle properties of parameter estimation are established, illustrating the latent subgroups can be consistently identified. Finally, we conduct numerical simulations and the analysis of a randomized trial on reduced nicotine standards for cigarettes to evaluate the performance of the proposed method.

报告人简介：

张伟平，中国科学技术大学教授、博导，任管理学院副院长。中国现场统计研究会常务理事，全国工业统计教学研究会副会长。近年来在纵向数据分析中的统计推断方法、贝叶斯建模与计算、网络数据分析等方面开展研究，发表学术论文60多篇，其中4篇论文发表在统计学四大顶刊上。近五年主持了国家自然科学基金面上项目，参与国家自然科学基金委重点项目等。获得安徽省教学名师，安徽省省级教学成果奖特等奖一项和一等奖两项。