Titre :

Consistency of maximum-likelihood and variational estimators in the Stochastic Block Model

Auteur(s) :

Celisse, Alain [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Daudin, J.-J. [Auteur]
Mathématiques et Informatique Appliquées [MIA-Paris]
Pierre, Laurent [Auteur]
Université Paris Nanterre - UFR Sciences économiques, gestion, mathématiques, informatique [UPN SEGMI]

Mot(s)-clé(s) en anglais :

Random graphs
stochastic block model
variational approximation
maximum-likelihood
concentration inequalities

Discipline(s) HAL :

Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]

Résumé en anglais : [en]

The stochastic block model (SBM) is a probabilistic model de- signed to describe heterogeneous directed and undirected graphs. In this paper, we address the asymptotic inference on SBM by use of maximum- likelihood and ...
Lire la suite >The stochastic block model (SBM) is a probabilistic model de- signed to describe heterogeneous directed and undirected graphs. In this paper, we address the asymptotic inference on SBM by use of maximum- likelihood and variational approaches. The identi ability of SBM is proved, while asymptotic properties of maximum-likelihood and variational esti- mators are provided. In particular, the consistency of these estimators is settled, which is, to the best of our knowledge, the rst result of this type for variational estimators with random graphs.Lire moins >

Langue :

Anglais

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL

Date de dépôt :

2025-01-24T10:29:27Z