Open Access
2017 Basic models and questions in statistical network analysis
Miklós Z. Rácz, Sébastien Bubeck
Statist. Surv. 11: 1-47 (2017). DOI: 10.1214/17-SS117


Extracting information from large graphs has become an important statistical problem since network data is now common in various fields. In this minicourse we will investigate the most natural statistical questions for three canonical probabilistic models of networks: (i) community detection in the stochastic block model, (ii) finding the embedding of a random geometric graph, and (iii) finding the original vertex in a preferential attachment tree. Along the way we will cover many interesting topics in probability theory such as Pólya urns, large deviation theory, concentration of measure in high dimension, entropic central limit theorems, and more.


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Miklós Z. Rácz. Sébastien Bubeck. "Basic models and questions in statistical network analysis." Statist. Surv. 11 1 - 47, 2017.


Received: 1 September 2016; Published: 2017
First available in Project Euclid: 8 September 2017

zbMATH: 06790046
MathSciNet: MR3696007
Digital Object Identifier: 10.1214/17-SS117

Primary: 05C80 , 60C05 , 62-02

Keywords: Community detection , evolving random graphs , networks , preferential attachment , Random geometric graphs , Random graphs , Random trees , statistical inference , Stochastic block model

Vol.11 • 2017
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