SBMSplitMerge

Inference in a Bayesian framework for a generalised stochastic block model. The generalised stochastic block model (SBM) can capture group structure in network data without requiring conjugate priors on the edge-states. Two sampling methods are provided to perform inference on edge parameters and block structure: a split-merge Markov chain Monte Carlo algorithm and a Dirichlet process sampler. Green, Richardson (2001) doi:10.1111/1467-9469.00242; Neal (2000) doi:10.1080/10618600.2000.10474879; Ludkin (2019) doi:10.48550/arXiv.1909.09421.

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