Efficient Bayesian inference for multiple network data

Francesco Barile; Sara Capozio; Bernardo Nipoti

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arXiv · 2610.01532

Efficient Bayesian inference for multiple network data

Francesco Barile·Sara Capozio·Bernardo Nipoti

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Abstract

We investigate distributional properties of the centered Erdős--Rényi distribution (Lunagòmez et al., 2021) and propose a semi-conjugate Bayesian approach to multiple network data. In simulations, both Gibbs sampling and empirical Bayes accurately recover network summaries, with the latter scaling efficiently with network size. As a companion to this note, we provide the R package BayesCER, which implements the proposed methodology.

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Francesco Barile, Sara Capozio, Bernardo Nipoti. 2026-10-01. Efficient Bayesian inference for multiple network data. https://arxiv.org/abs/2610.01532

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