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Bayesian model selection for the latent position cluster model for social networks
2017
Network Science
The latent position cluster model is a popular model for the statistical analysis of network data. This model assumes that there is an underlying latent space in which the actors follow a finite mixture distribution. Moreover, actors which are close in this latent space are more likely to be tied by an edge. This is an appealing approach since it allows the model to cluster actors which consequently provides the practitioner with useful qualitative information. However, exploring the
doi:10.1017/nws.2017.6
fatcat:3bl3jpalxrehroym2lgahcj6pi