Multiple change points detection and clustering in dynamic networks

DOI10.1007/s11222-017-9775-1zbMath1405.62076OpenAlexW2724643438MaRDI QIDQ1616777

Pierre Latouche, Marco Corneli, Fabrice Rossi

Publication date: 7 November 2018

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-017-9775-1

zbMATH Keywords

clusteringdynamic networksstochastic block modelPELTnon-homogeneous Poisson point processesvariational EM

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Stochastic network models in operations research (90B15)

Related Items (3)

Poisson degree corrected dynamic stochastic block model ⋮ Model-based clustering of time-evolving networks through temporal exponential-family random graph models ⋮ The dynamic stochastic topic block model for dynamic networks with textual edges

Uses Software

• Rambo

Cites Work

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