文章基本信息

标题：A nonparametric view of network models and Newman–Girvan and other modularities
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作者：Peter J. Bickel ; Aiyou Chen
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2009
卷号：106
期号：50
页码：21068-21073
DOI：10.1073/pnas.0907096106
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Prompted by the increasing interest in networks in many fields, we present an attempt at unifying points of view and analyses of these objects coming from the social sciences, statistics, probability and physics communities. We apply our approach to the Newman-Girvan modularity, widely used for "community" detection, among others. Our analysis is asymptotic but we show by simulation and application to real examples that the theory is a reasonable guide to practice.
关键词：modularity ; profile likelihood ; ergodic model ; spectral clustering