A semiparametric extension of the stochastic block model for longitudinal networks

DOI10.1093/biomet/asy016zbMath1499.62213arXiv1512.07075OpenAlexW4300525856WikidataQ130134995 ScholiaQ130134995MaRDI QIDQ4561018

Catherine Matias, Fanny Villers

Publication date: 10 December 2018

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1512.07075

zbMATH Keywords

semiparametric modelexpectation-maximization algorithmvariational approximationtemporal networkdynamic interactionlink streamlongitudinal network

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (10)

Multiple change points detection and clustering in dynamic networks ⋮ Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance ⋮ Network dynamics with a nested node set: Sociability in seven villages in Senegal ⋮ Poisson degree corrected dynamic stochastic block model ⋮ A dynamic network model to measure exposure concentration in the Austrian interbank market ⋮ Mining the hidden link structure from distribution flows for a spatial social network ⋮ Online estimation and community detection of network point processes for event streams ⋮ A dynamic stochastic blockmodel for interaction lengths ⋮ Mixture of hidden Markov models for accelerometer data ⋮ Dynamic stochastic block models: parameter estimation and detection of changes in community structure

This page was built for publication: A semiparametric extension of the stochastic block model for longitudinal networks