Markov Chain Monte Carlo Estimation of Exponential Random Graph Models

@article{Snijders2002MarkovCM,
  title={Markov Chain Monte Carlo Estimation of Exponential Random Graph Models},
  author={Tom A. B. Snijders},
  journal={Journal of Social Structure},
  year={2002},
  volume={3}
}
This paper is about estimating the parameters of the exponential random graph model, also known as the p∗ model, using frequentist Markov chain Monte Carlo (MCMC) methods. The exponential random graph model is simulated using Gibbs or MetropolisHastings sampling. The estimation procedures considered are based on the Robbins-Monro algorithm for approximating a solution to the likelihood equation. A major problem with exponential random graph models resides in the fact that such models can have… CONTINUE READING
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