讲座题目:An Eigengap Ratio Test for Determining the Number of Communities in Network Data
演讲嘉宾:兰伟,西南财经大学统计学院副院长,西南财经大学“光华杰出学者计划”青年杰出教授
主持人:李好 助理教授 皇冠hg1088官方官网数量经济研究所、南开大学经济行为与政策模拟实验室
演讲嘉宾简介:兰伟,博士,西南财经大学统计学院副院长,教授,博士生导师,北京大学商务智能研究中心研究员。2009年本科毕业于南开大学数学学院,2013年博士毕业于北京大学光华管理学院后加入西南财经大学统计学院,西南财经大学“光华杰出学者计划”青年杰出教授。主持国家自然科学基金优秀青年科学基金项目、面上项目和多个重点项目子课题。在Journal of the American Statistical Association, Annals of Statistics, Journal of Econometrics, Journal of Business & Economic Statistics,《经济学季刊》等国内国际知名学术期刊发表中论文40余篇。
讲座摘要:To characterize the community structure in network data, researchers have introduced various block-type models, including the stochastic block model, degree-corrected stochastic block model, mixed membership block model, degree-corrected mixed membership block model, and others. A critical step in applying these models effectively is determining the number of communities in the network. However, to our knowledge, existing methods for estimating the number of network communities often require model estimations or are unable to simultaneously account for network sparsity and a divergent number of communities. In this paper, we propose an eigengap-ratio based test that address these challenges. The test is straightforward to compute, requires no parameter tuning, and can be applied to a wide range of block models without the need to estimate network distribution parameters. Furthermore, it is effective for both dense and sparse networks with a divergent number of communities. We show that the proposed test statistic converges to a function of the type-I Tracy-Widom distributions under the null hypothesis, and that the test is asymptotically powerful under alternatives. Simulation studies on both dense and sparse networks demonstrate the efficacy of the proposed method. Three real world examples are presented to illustrate the usefulness of the proposed test.
时间:2024年10月22日(周二)下午14:00
地点:皇冠hg1088官方官网高层10楼会议室
主办单位:皇冠hg1088官方官网、南开大学经济行为与政策模拟实验室
编辑:徐牧谣、李嫦娟
审核:蒋殿春、卢彤菲、孙景宇