Consistency of maximum-likelihood and ...
Document type :
Pré-publication ou Document de travail
Title :
Consistency of maximum-likelihood and variational estimators in the Stochastic Block Model
Author(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]
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]
English keyword(s) :
Random graphs
stochastic block model
variational approximation
maximum-likelihood
concentration inequalities
stochastic block model
variational approximation
maximum-likelihood
concentration inequalities
HAL domain(s) :
Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]
Statistiques [stat]/Théorie [stat.TH]
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
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Anglais
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