Disentangling group and link persistence in dynamic stochastic block models

DOI10.1088/1742-5468/AAEB44zbMath1457.90036arXiv1701.05804OpenAlexW2962929315WikidataQ128775821 ScholiaQ128775821MaRDI QIDQ3303275

Paolo Barucca, Daniele Tantari, Piero Mazzarisi, Fabrizio Lillo

Publication date: 11 August 2020

Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1701.05804

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Stochastic network models in operations research (90B15)

Related Items (3)

Persistence in complex systems ⋮ A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market ⋮ Relating Modularity Maximization and Stochastic Block Models in Multilayer Networks

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