Two-Mode Network Autoregressive Model

发布者:季洁发布时间:2019-12-12浏览次数:226

Speaker:黄丹阳 副教授 中国人民大学
Host:Rujun Jiang, School of Data Science, Fudan University
Time:10:30-11:30, Dec 12, 2019
Location:Zibin N201, Fudan University
Abstract:

A two-mode network refers to a network where the nodes are classified into two distinct types and edges can only exist between nodes of different types. In analysis of two-mode networks, one important objective is to explore the relationship between responses of two types of nodes. To this end, we propose a network autoregressive model for two-mode networks. Different network autocorrelation coefficients are allowed. To estimate the model, a quasi-maximum likelihood estimator is developed with high computational cost. To alleviate the computational burden, a least squares estimator is proposed, which is applicable in large-scale network. The theoretical properties of both estimators are investigated. The finite sample performances are assessed through simulations and a real data example.

Bio:
黄丹阳,中国人民大学统计学院副教授,北京大学光华管理学院博士。研究兴趣为超高维数据分析,社交网络数据建模,互联网征信数据分析等。研究论文发表于在Journal of Econometrics, Journal of Business and Economic Statistics,Electronic Journal of Statistics, Statistica Sinica以及管理世界等国内外期刊。在互联网征信领域具有丰富的实践及研究经验,主持多项相关纵向科研课题。