报告人/Speaker: 张文扬 教授, 英国约克大学
报告题目/Title: Homogeneity Pursuit in Single Index Models based Panel Data Analysis
时间/Date & Time: July 9, 2018,10:00-11:00
Panel data analysis is an important topic in statistics and econometrics. Traditionally, in panel data analysis, all individuals are assumed to share the same unknown parameters, e.g. the same coefficients of covariates when the linear models are used, and the differences between the individuals are accounted for by cluster effects. This kind of modelling only makes sense if our main interest is on the global trend, this is because it would not be able to tell us anything about the individual attributes which are sometimes very important. In this talk, I will present a new modelling approach, based on the single index models embedded with homogeneity, for panel data analysis, which builds the individual attributes in the model and is parsimonious at the same time. I will show a data driven approach to identify the structure of homogeneity, and estimate the unknown parameters and functions based on the identified structure. I will show the asymptotic properties of the resulting estimators. I will also use intensive simulation studies to show how well the resulting estimators work when sample size is finite. Finally, I will apply the proposed modelling idea to a public financial dataset and a UK climate dataset, and show some interesting findings.
报告人简介/About the speaker:
张文扬教授是英国顶尖大学约克大学的统计学首席教授。张文扬教授主要从事大数据分析，金 融数据分析，高维数据分析，非参数建模、时间序列分析、空间数据分析，多层次建模，生存分析，结构方程模型等方向的研究。曾先后在英国伦敦政治经济学院、英国 Kent 大学、英国 Bath 大学、英国 York 大学任教，现为英国 York 大学统计学首席教授。他曾是英国皇家统计学会科研委员会委员(历史上仅有三位华人担任该委员会委员)，曾经连续担任三届统计学三大国际顶尖期刊之一 Journal of the American Statistical Association 的副主编。