建院40周年系列活动之学术讲座第十二期
统计学系列Seminar第69期
主题: Spatially Clustered Varying Coefficient Model
主讲人: 唐炎林
地点：威尼斯欢迎你welcome（中惠楼）102会议室
会议时间：2020年9月17日上午10:00-11:00
摘要: In various applications with large spatial regions, the relationship between the response variable and the covariates is expected to exhibit complex spatial patterns. We propose a spatially clustered varying coefficient model, where the regression coefficients are allowed to vary smoothly within each cluster but change abruptly across the boundaries of adjacent clusters, and we develop a unified approach for simultaneous coefficient estimation and cluster identification. The coefficients are approximated by penalized splines, and the clusters are identified through a fused concave penalty on differences in neighboring locations, where the spatial neighbors are specified by the minimum spanning tree (MST). The optimization is solved efficiently by the alternating direction method of multipliers, using the sparsity structure from MST. Furthermore, we establish the oracle property of the proposed method considering the structure of MST. Numerical studies show that the proposed method can efficiently incorporate spatial neighborhood information and automatically detect possible spatially clustered patterns in the regression coefficients. An empirical study in oceanography illustrates that the proposed method is promising to provide informative results.
主讲人简介
唐炎林，华东师范大学统计学院研究员，博士生导师。2012年1月于复旦大学统计系获得博士学位，师从朱仲义教授。2012年5月起在同济大学数学系工作，历任讲师、副教授，2019年1月加入华东师范大学统计学院。读博、工作期间曾访问何旭铭教授一年，王会霞教授两年，多次访问香港中文大学宋心远教授。主要研究方向为分位数回归、高维数据统计推断、删失数据，主持国家自然科学基金面上项目、青年项目各一项，上海市浦江人才计划一项，在Biometrika、PNAS、Statistica Sinica、Biometrics等SCI期刊发表论文二十余篇。目前担任国际SCI期刊Journal of Korean Statistical Society的副主编。
