Bayesian Analysis

Bayesian Community Detection

S. L. van der Pas and A. W. van der Vaart

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Abstract

We introduce a Bayesian estimator of the underlying class structure in the stochastic block model, when the number of classes is known. The estimator is the posterior mode corresponding to a Dirichlet prior on the class proportions, a generalized Bernoulli prior on the class labels, and a beta prior on the edge probabilities. We show that this estimator is strongly consistent when the expected degree is at least of order log2n, where n is the number of nodes in the network.

Article information

Source
Bayesian Anal. (2017), 30 pages.

Dates
First available in Project Euclid: 19 October 2017

Permanent link to this document
https://projecteuclid.org/euclid.ba/1508378465

Digital Object Identifier
doi:10.1214/17-BA1078

Subjects
Primary: 62F15: Bayesian inference 90B15: Network models, stochastic

Keywords
stochastic block model community detection networks consistency Bayesian inference modularities MAP estimation

Rights
Creative Commons Attribution 4.0 International License.

Citation

van der Pas, S. L.; van der Vaart, A. W. Bayesian Community Detection. Bayesian Anal., advance publication, 19 October 2017. doi:10.1214/17-BA1078. https://projecteuclid.org/euclid.ba/1508378465


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