A general core-periphery strength parameter, label recovery guarantees, and two hypothesis tests distinguish intrinsic core-periphery structure from degree-driven artifacts.
Statistical Network Analysis: Past, Present, and Future
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abstract
This article provides a brief overview of statistical network analysis, a rapidly evolving field of statistics, which encompasses statistical models, algorithms, and inferential methods for analyzing data in the form of networks. Particular emphasis is given to connecting the historical developments in network science to today's statistical network analysis, and outlining important new areas for future research. This invited article is intended as a book chapter for the volume "Frontiers of Statistics and Data Science" edited by Subhashis Ghoshal and Anindya Roy for the International Indian Statistical Association Series on Statistics and Data Science, published by Springer. This review article covers the material from the short course titled "Statistical Network Analysis: Past, Present, and Future" taught by the author at the Annual Conference of the International Indian Statistical Association, June 6-10, 2023, at Golden, Colorado.
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Statistical inference for core-periphery structures
A general core-periphery strength parameter, label recovery guarantees, and two hypothesis tests distinguish intrinsic core-periphery structure from degree-driven artifacts.