Consistency of maximum-likelihood and ...
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Article dans une revue scientifique: Article original
DOI :
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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, Jean-Jacques [Auteur]
Mathématiques et Informatique Appliquées [MIA-Paris]
Pierre, Laurent [Auteur]

Laboratoire Paul Painlevé - UMR 8524 [LPP]
Daudin, Jean-Jacques [Auteur]
Mathématiques et Informatique Appliquées [MIA-Paris]
Pierre, Laurent [Auteur]
Journal title :
Electronic Journal of Statistics
Pages :
1847-1899
Publisher :
Shaker Heights, OH : Institute of Mathematical Statistics
Publication date :
2012
ISSN :
1935-7524
English keyword(s) :
concentration inequalities
random graphs
stochastic block model
maxi- mum likelihood estimators
variational estimators
consistency
random graphs
stochastic block model
maxi- mum likelihood estimators
variational estimators
consistency
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 designed to describe heterogeneous directed and undirected graphs. In this paper, we address the asymptotic inference in SBM by use of maximum-likelihood and ...
Show more >The stochastic block model (SBM) is a probabilistic model designed to describe heterogeneous directed and undirected graphs. In this paper, we address the asymptotic inference in SBM by use of maximum-likelihood and variational approaches. The identifiability of SBM is proved while asymptotic properties of maximum-likelihood and variational estimators are derived. In particular, the consistency of these estimators is settled for the probability of an edge between two vertices (and for the group proportions at the price of an additional assumption), which is to the best of our knowledge the first result of this type for variational estimators in random graphs.Show less >
Show more >The stochastic block model (SBM) is a probabilistic model designed to describe heterogeneous directed and undirected graphs. In this paper, we address the asymptotic inference in SBM by use of maximum-likelihood and variational approaches. The identifiability of SBM is proved while asymptotic properties of maximum-likelihood and variational estimators are derived. In particular, the consistency of these estimators is settled for the probability of an edge between two vertices (and for the group proportions at the price of an additional assumption), which is to the best of our knowledge the first result of this type for variational estimators in random graphs.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Non spécifiée
Popular science :
Non
Comment :
AMS 2000 subject classifications: Primary 62G05, 62G20; secondary 62E17, 62H30.
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Source :
Submission date :
2025-01-24T16:44:24Z
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