光華講壇——社會名流與企業家論壇第6589期

主題：Nonlinear dependence metrics and their statistical applications 非線性相依度量及其統計應用（系列講座）

主講人：伊利諾伊大學厄巴納-香檳分校 邵曉峰教授

主持人：西南財經大學統計學院 常晉源教授

時間：6月26日 8:30-12:00  6月27日 8:30-12:00  6月28日 8:30-12:00

舉辦地點：西南財經大學光華校區光華裙樓2303

主辦單位：數據科學與商業智能聯合實驗室 統計學院 科研處

主講人簡介：

Xiaofeng Shao received his PhD in Statistics from the University of Chicago in 2006 and has since been a faculty member with the Department of Statistics at the University of Illinois Urbana-Champaign. His current research interests include time series analysis, change-point analysis, functional data analysis, high dimensional data analysis and their applications. He is a fellow of Institute of Mathematical Statistics (IMS) and American Statistical Association (ASA). He currently serves as an associate editor for Journal of Royal Statistical Society, Series B and Journal of Time Series Analysis.

邵曉峰于2006年在芝加哥大學獲得統計學博士學位，此后一直在伊利諾伊大學厄巴納-香檳分校統計系任教。他目前的研究興趣包括時間序列分析、變點分析、函數型數據分析、高維數據分析及其應用。他是當選的ASA和IMS成員，目前擔任Journal of Royal Statistical Society, Series B和Journal of Time Series Analysis的副主編。

內容簡介：

In these talks, we aim to provide an introduction of nonlinear dependence metrics and their statistical applications. Emphasis will be placed on distance covariance, energy distance and their variants, including Hilbert-Schmidt Independence Criterion, maximum mean discrepancy, martingale difference divergence, among others. The usefulness of these metrics will be demonstrated in some contemporary problems in statistics, such as dependence testing and variable screening/selection for high-dimensional data, as well as dimension reduction and diagnostic checking for multivariate time series. Some recent work on their applications to the inference of non-Euclidean data will also be discussed. The presentations are based on the research results I have obtained in the past and will cover methodology, theory and practical data examples.

在本系列講座中，我們旨在介紹非線性相依度量及其統計應用，將重點講距離協方差、能量距離及其變體，包括希爾伯特-施密特獨立準則、最大均值差異、鞅差發散等。這些度量將在統計學的一些當代問題中得到應用，如高維數據的相依度量和變量篩選/選擇，以及多變量時間序列的降維和檢測。此外，還將討論將這些指標應用于非歐幾里得數據推斷的一些最新工作。以上內容是基于我過去取得的研究成果，將涵蓋方法論、理論和實際數據示例。