题 目：Statistical Clustering of SemiparametricLongitudinal Networksthrough Stochastic Snapshots

主讲人：赵晓兵教授

时 间：2021年5月20日（周四）13：30-14：30

地 点：6号学院楼402会议室

主办单位：002cc白菜资讯 浙江省2011“数据科学与大数据分析协同创新中心”

主讲人简介：

赵晓兵，002cc白菜资讯教授，博士生导师，浙江省高校中青年学科带头人。2006.12博士毕业于香港理工大学，2008.10年在华东师范大学统计学院博士后出站，多次访问澳大利亚麦考瑞大学精算系和美国西北大学预防医学系。主要研究方向为应用统计学（保险精算学、生存分析等），已经公开发表论文50多篇，其中SCI(SSCI)收录论文34篇，主持国家级项目3项，主持省部级项目4项。

摘要：

The analysis of dynamic network data based on statistical models has attracted wide attention in social and biological research fields, where the interactions between individuals mayundertake large and systematic changes. In this paper, we propose a statistical model for therecurrent events of instantaneous interactions between the nodes, in which a Poisson processwith a semiparametric mean function of recurrent interactions is considered under the condition of latent membership of the nodes. A joint model of the recurrent interaction processand discrete-time observation process is proposed to characterize the impact of the time-slicesfor the snapshots. A variational expectation-maximization algorithm is applied to obtain theestimators of the connectivity parameters and the latent variables. The asymptotic propertiesof the estimates are also discussed. Some simulation studies and applications on real data arepresented to illustrate the performance of the proposed models and methodology.

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