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New Approaches to Statistical Learning of Modern Time Series

作者: 发布时间:2023-10-11 点击数:
主讲人:陈嵘
主讲人简介:

陈嵘,美国罗格斯大学统计系特聘教授、系主任,其研究领域包括非线性和高维时间序列分析、蒙特卡罗方法、统计在生物信息学、商业、经济学以及工程学中的应用等,美国统计协会会士、数理统计学会会士、国际统计学会当选会员,目前担任Statistica Sinica联合主编,曾担任Journal of Business and Economic Statistics联合主编。

主持人:林明
讲座简介:

The BIGDATA era, many new forms of data have become available and useful in various important applications. When these data are observed over time, they form new types of time series that require new statistical models and analytical tools in order to extract useful information. In this talk we present new developments in analyzing matrix/tensor time series, dynamic networks, functional time series and compositional time series, with applications ranging from economics, finance, international trade, electricity loading and others. We will also briefly discuss approaches on modeling other forms of time series, including text time series and dynamic social networks.  

时间:2023-10-16 (Monday) 16:40-18:00
地点:经济楼N302
讲座语言:中文
主办单位:太阳成tyc7111cc研究生院、太阳成tyc7111cc、王亚南经济研究院、邹至庄经济研究院
承办单位:太阳成tyc7111cc、王亚南经济研究院、邹至庄经济研究院
期数:太阳成tyc7111cc群贤学科学术讲座
联系人信息:许老师,电话:0592-2182991,邮箱:ysxu@xmu.edu.cn
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