Weighted stochastic block model.
Stat Methods Appt
; 30(5): 1365-1398, 2021.
Article
em En
| MEDLINE
| ID: mdl-34840548
ABSTRACT
We propose a weighted stochastic block model (WSBM) which extends the stochastic block model to the important case in which edges are weighted. We address the parameter estimation of the WSBM by use of maximum likelihood and variational approaches, and establish the consistency of these estimators. The problem of choosing the number of classes in a WSBM is addressed. The proposed model is applied to simulated data and an illustrative data set.
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Base de dados:
MEDLINE
Idioma:
En
Revista:
Stat Methods Appt
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Irlanda