题目：Autoregressive Networks

主讲人：伦敦政治经济学院 姚琦伟教授

主持人：西南财经大学统计学院 常晋源教授

时间：2023年8月3日（周四）上午09:00-12:00

          2023年8月4日（周五）下午14:00-17:00

          2023年8月7日（周一）上午09:00-12:00

          2023年8月8日（周二）下午14:00-17:00

地点：西南财经大学光华校区光华楼1003会议室

报告摘要：

We propose a first-order autoregressive (i.e. AR(1)) model for dynamic network processes in which edges change over time while nodes remain unchanged. The model depicts the dynamic changes explicitly. It also facilitates simple and efficient statistical inference methods including a permutation test for diagnostic checking for the fitted network models. The proposed model can be applied to the network processes with various underlying structures but with independent edges. As an illustration, an AR(1) stochastic block model has been investigated in depth, which characterizes the latent communities by the transition probabilities over time. This leads to a new and more effective spectral clustering algorithm for identifying the latent communities. We have derived a finite sample condition under which the perfect recovery of the community structure can be achieved by the newly defined spectral clustering algorithm. Furthermore the inference for a change point is incorporated into the AR(1) stochastic block model to cater for possible structure changes. We have derived the explicit error rates for the maximum likelihood estimator of the change-point. Application with three real data sets illustrates both relevance and usefulness of the proposed AR(1) models and the associate inference methods.

主讲人简介：

姚琦伟教授，英国伦敦政治经济学院统计系教授，英国皇家统计学会会士，美国统计协会会士，数理统计学会会士，国际统计研究学会选举会员，泛华统计学会会员。主要研究领域为时间序列分析、高维时间序列建模和预测、降维和因子建模等。迄今已在AoS、Biometrika、Econometrica、JoE、JASA和JRSSB等期刊上发表学术论文90多篇，并获得EPSRC、BBSRC等英国国家基金会支持的多项研究基金项目。目前担任JRSSB的联合主编，曾担任AoS、JBES、JASA和Statistica Sinica等期刊的副主编和联合主编。