- We consider relaxing the homogeneity assumption in exponential family random graph models (ERGMs) using binary latent class indicators. This may be interpreted as combining a posteriori blockmodelling with ERGMs, relaxing the independence assumptions of the former and the homogeneity assumptions of the latter. We propose a Markov chain Monte Carlo algorithm for drawing from the joint posterior of the model parameters and latent class indicators.
- pp. 845-849
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Edited volume (collection of essays published as book)
"Proceedings of the 6th St. Petersburg Workshop on