A note on perfect simulation for Exponential Random Graph Models

Andressa Cerqueira, Aurélien Garivier and Florencia Leonardi

In this paper, we propose a perfect simulation algorithm for the Exponential Random Graph Model, based on the Coupling from the past method of Propp and Wilson (1996). We use a Glauber dynamics to construct the Markov Chain and we prove the monotonicity of the ERGM for a subset of the parametric space. We also obtain an upper bound on the running time of the algorithm that depends on the mixing time of the Markov chain.

The whole paper is available here.

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