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