数学科学学院学术报告[2023] 103号
(高水平大学建设系列报告875号)
报告题目:Subgroup learning in functional-on-scalar regression under the RKHS framework
报告人：尤进红教授
报告时间：2023年12月21日 16:00-17：00
讲座地点：汇星楼514
报告内容：Motivated by the potential heterogeneity in functional or image data, we utilize a change-plane analysis for subgroup learning in functional or image responses. This method is applicable to estimate, identify, and test the existence of subgroups in the functional-on-scalar models. We fit the proposed model within a Reproducing Kernel Hilbert Space (RKHS) framework and develop an iterative procedure to obtain the estimates of coefficient functions and change-plane parameters. The asymptotic properties of the resultant estimators are derived through a smoothing method. Furthermore, we introduce a novel score-type statistic for testing the presence of subgroups in functional data and develop a resampling procedure to approximate the distribution of the test statistic. We establish the asymptotic properties of the test statistic under both the null hypothesis and local alternative hypotheses. Numerical studies are conducted to illustrate the finite-sample performance of the proposed estimation and testing methods. An application to Alzheimer’s Disease Neuroimaging Initiative data and COVID-19 data is also provided.报告人简介：尤进红教授， 加拿大女皇大学（University of Regina）统计学博士，美国北卡罗纳教堂山分校博士后， 上海财经大学统计与管理学院tenured常任轨教授、博士生导师和统计与数据科学研究院副院长，全国工业统计学教学研究会第九届理事会副会长，全国统计学交叉学科分会副会长，曾任Quality Technology and Quantitative Management (QTQM), special issue: Mathematical and Statistical Finance的客座编委（Guest Editor）。 尤进红教授有十余年的北美学习、工作经历。长期从事计量经济学、数理统计以及生物统计的科学研究； 在面板数据、函数型数据数据分析及其在经济学， 金融学和生物医学方面的应用开展了许多有价值的研究工作；在国际和国内著名的统计学、经济学和数据科学杂志（包括Journal of the American Statistical Association，Journal of Econometric，Journal of Machine Learning Research等）上发表学术论文八十余篇，其中三大检索论文六十余篇，被SCI他引几百余次；主持和参与了多个国家自科基金项目；培养了将近四十位的博士生和博士后。为国际著名统计和计量经济学杂志Annals of Statistics, Journal of the American Statistical Association , Biometrika和Journal of Econometric等的论文评审人。曾获上海市教委教学成果一等奖等。
数学科学学院
2023年12月18日
