时 间:2023年9月1日(周五)16:00-17:00
主持人:复旦大学 管理学院 统计与数据科学系 黎德元 教授
地 点:思源教授楼726室
报告人:Prof. Chen Zhou
Erasmus University Rotterdam(荷兰)
题 目:Graphical Lasso for Extremes
摘 要:In this paper we estimate the sparse dependence structure in the tail region of a multivariate random vector, potentially of high dimension. The tail dependence is modeled via a graphical model for extremes embedded in the Huesler-Reiss distribution (Engelke and Hitz, 2020). We propose the extreme graphical lasso procedure to estimate the sparsity in the tail dependence, similar to the Gaussian graphical lasso in high dimensional statistics. We prove its consistency in identifying the graph structure and estimating model parameters. The efficiency and accuracy of the proposed method are illustrated in simulated and real examples.
个人简介:Prof. Chen Zhou is Professor of Mathematical Statistics and Risk Management at Erasmus University Rotterdam. His research focuses on extreme value statistics and quantitative risk management. His statistical work appears in Annals of Statistics, Journal of the Royal Statistical Society (Series B), Journal of American Statistical Association, Biometrika, among others. In addition, his research spans to the field of finance and economics, and has been published in leading journals including Journal of Financial and Quantitative Analysis and Journal of Economic Theory. Chen Zhou serves as the Area Editor of Economics, Finance and Insurance at the journal Extremes. He received his PhD (2008) from Erasmus University Rotterdam, after completing his Bachelor (2001) and Master (2003) degrees at Peking University.
统计与数据科学系
2023-8-31
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