Approximate Variational Estimation for a Model of Network Formation
نویسندگان
چکیده
Abstract We develop approximate estimation methods for exponential random graph models (ERGMs), whose likelihood is proportional to an intractable normalizing constant. The usual approach approximates this constant with Monte Carlo simulations; however, convergence may be exponentially slow. propose a deterministic method, based on variational mean-field approximation of the ERGM's compute lower and upper bounds error any network size, adapting nonlinear large deviation results. This translates into distance between true likelihood. simulations suggest that in practice, our method performs better than conservative theoretical imply, class models.
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ژورنال
عنوان ژورنال: The Review of Economics and Statistics
سال: 2023
ISSN: ['0034-6535', '1530-9142']
DOI: https://doi.org/10.1162/rest_a_01023