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香港大学 姚建峰教授: Large sample covariance matrices and applications

([永盈会新闻] 发布于 :2017-12-25 )

光华讲坛——社会名流与企业家论坛第4806

 

 Large sample covariance matrices and applications

主讲人:香港大学 姚建峰教授

主持人:统计学院 林华珍教授

20171226日(星期二)下午4:00-5:00

:弘远楼会议室408

主办单位:统计研究中心  统计学院   科研处

 

主讲人简介:

Jianfeng Yao is a professor of Department Statistics and Actuarial Science at The University of Hong Kong. His current research work is concentrated in the field of the theory of random matrices and their applications to high-dimensional statistics. In collaborations with Prof. Zhidong Bai, he has been working on limit theorems for eigenvalue distributions of large dimensional random matrices, especially Wigner matrices and sample covariance matrices.

His other research interests include

i) Statistics of stochastic processes: nonlinear time series, Markov-switching processes

ii) Understanding and probabilistic modelling of digital images

Now, he is the associate editor of the Random Matrices: Theory and Applications and ESAIM: Proceedings.Moreover, he has published a book called Large Sample Covariance Matrices and High-Dimensional Data Analysis in March 2015.

        More details please browse the web http://web.hku.hk/~jeffyao/

主要内容:

This talk is a survey on recent results from random matrix theory on large sample covariance matrices. Some key ideas and results meaningful for high-dimensional statistics will be detailed. Significant applications to hypothesis testing on large sample covariance matrix and factor models will be presented.



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