| 主讲人 |
Zhou Zhou |
简介 |
<p>We study general distributional change point analysis for high-dimensional time series under nonstationary temporal dependence and limited computational resources. To mitigate noise accumulation from irrelevant coordinates and reduce the computational cost, we propose a sparse random projection procedure based on characteristic functions. We quantify the computational complexity of the random projections and show that the required number of projections grows polynomially with the ambient dimension. To accommodate nonstationary temporal dependence, a Gaussian multiplier bootstrap based on contrasts of local empirical characteristic functions is developed. We establish asymptotic false detection control and simultaneous guarantees for estimating the number and locations of multiple change points, with a near-parametric uniform localization rate up to logarithmic factors. A key technical innovation is a Gaussian approximation for high-dimensional multi-scale sparse time series, which is of independent interest. Simulation studies demonstrate the effectiveness of the proposed procedure in detecting and localizing distributional changes under various temporal dependence structures. An application to neural recordings further illustrates the practical utility of the proposed method in detecting diverse distributional changes in neural activity.</p> |
| 时间 |
2026-11-18 (Wednesday) 16:40-18:00 |
地点 |
Room N302, Economics Building |
| 讲座语言 |
English |
主办单位 |
厦门大学经济学院、王亚南经济研究院、邹至庄经济研究院 |
| 承办单位 |
厦门大学经济学院、王亚南经济研究院、邹至庄经济研究院 |
类型 |
系列讲座 |
| 联系人信息 |
叶老师，电话2181098，邮箱yhye.wise@xmu.edu.cn |
主持人 |
Muyi Li |
| 专题网站 |
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专题 |
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| 主讲人简介 |
<p>Zhou Zhou is Qiushi Chair Professor at Zhejiang University and has been selected for a national high-level talent program in China. He received his B.S. in Mathematics from Peking University in 2003 and his Ph.D. in Statistics from the University of Chicago in 2009. From 2009 to 2026, he served on the faculty of the Department of Statistical Sciences at the University of Toronto, where he held successive appointments as Assistant Professor, tenured Associate Professor, and tenured Full Professor. His academic achievements have been recognized with several prestigious awards, including the NSERC Discovery Accelerator Award in 2021 and the CRM–SSC Prize in Statistics in 2023. In 2026, he returned to China to join the Center for Data Science at Zhejiang University. His research interests include complex spatiotemporal data analysis, nonparametric statistical methods, time-frequency analysis, resampling methods, and change-point analysis. He has published extensively in leading journals in statistics, econometrics, and information theory, and his research has received support from prestigious research institutions. </p> |
期数 |
高级计量经济学与统计学系列讲座2026年秋季学期第七讲（总211讲） |
