SBMSplitMerge: Inference for a Generalised SBM with a Split Merge Sampler
Matthew Ludkin · 2020
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) ; Neal (2000) ; Ludkin (2019) .