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September 2019 Sampling perspectives on sparse exchangeable graphs
Christian Borgs, Jennifer T. Chayes, Henry Cohn, Victor Veitch
Ann. Probab. 47(5): 2754-2800 (September 2019). DOI: 10.1214/18-AOP1320


Recent work has introduced sparse exchangeable graphs and the associated graphex framework, as a generalization of dense exchangeable graphs and the associated graphon framework. The development of this subject involves the interplay between the statistical modeling of network data, the theory of large graph limits, exchangeability and network sampling. The purpose of the present paper is to clarify the relationships between these subjects by explaining each in terms of a certain natural sampling scheme associated with the graphex model. The first main technical contribution is the introduction of sampling convergence, a new notion of graph limit that generalizes left convergence so that it becomes meaningful for the sparse graph regime. The second main technical contribution is the demonstration that the (somewhat cryptic) notion of exchangeability underpinning the graphex framework is equivalent to a more natural probabilistic invariance expressed in terms of the sampling scheme.


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Christian Borgs. Jennifer T. Chayes. Henry Cohn. Victor Veitch. "Sampling perspectives on sparse exchangeable graphs." Ann. Probab. 47 (5) 2754 - 2800, September 2019.


Received: 1 August 2017; Revised: 1 June 2018; Published: September 2019
First available in Project Euclid: 22 October 2019

zbMATH: 07145302
MathSciNet: MR4021236
Digital Object Identifier: 10.1214/18-AOP1320

Primary: 60C05
Secondary: 62D05 , 62G05 , 62G09

Keywords: Graph limits , network analysis , nonparametric estimation , sampling

Rights: Copyright © 2019 Institute of Mathematical Statistics


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Vol.47 • No. 5 • September 2019
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