时 间：2025年10月9日 15:00-16:00
地 点：普陀校区理科大楼A1514
报告人：李睿 上海对外经贸大学教授
主持人：唐炎林 华东师范大学教授
摘 要：
In this article, we study the quantile regression and homogeneity detection of a varying index coefficient panel data model with fixed individual effect that shows nonlinear time trend. Based on spline approximation, we get the estimates of trend function, link function and index parameters, and establish the convergence rate and asymptotic normality accordingly. Noting that the subjects within a group may share the same trend functions, which motivates us to further identify the possible homogeneity in this trend by integrating regularization with binary segmentation algorithm. For determining the thresholding parameter in homogeneity identification, we propose a generalized Bayesian information criterion following line in \cite{chen2019estimating}. Further, we propose a penalized method to identify the constant and linear structure of nonparametric functions in our model. Finally, we provide more efficient estimates via grouped observations and improve the large sample properties. Simulation studies and a real analysis of Air pollution data and Integrated surface data (APD$\&$ISD) are conducted to illustrate the finite sample performance of the proposed approach.
报告人简介：
上海对外经贸大学统计与数据科学学院教授，博士生导师。博士毕业于上海财经大学统计与数据科学学院统计学专业。主要从事统计学的理论、方法和应用研究，具体包括非参数/半参数建模、纵向/面板数据分析、测量误差、分位数回归等。主持国家社会科学基金一般项目、教育部人文社会科学研究规划基金项目、全国统计科学研究重点项目、教育部重点实验室项目和上海市科学技术委员会项目等，在统计学权威期刊Statistica Sinica、Scandinavian Journal of Statistics、Journal of Business & Economic Statistics、Journal of Computational and Graphical Statistics、Journal of Multivariate Analysis等发表学术论文30多篇。担任中国现场统计研究会大数据统计分会常务理事、全国工业统计学教学研究会民族统计与数据科学分会常务理事和统计交叉科学研究分会理事等。