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arXiv · 1309.5936

Nonparametric graphon estimation

Patrick J. Wolfe·Sofia C. Olhede
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Abstract

We propose a nonparametric framework for the analysis of networks, based on a natural limit object termed a graphon. We prove consistency of graphon estimation under general conditions, giving rates which include the important practical setting of sparse networks. Our results cover dense and sparse stochastic blockmodels with a growing number of classes, under model misspecification. We use profile likelihood methods, and connect our results to approximation theory, nonparametric function estimation, and the theory of graph limits.

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Patrick J. Wolfe, Sofia C. Olhede. 2013-09-23. Nonparametric graphon estimation. https://arxiv.org/abs/1309.5936

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