arXiv 3 Feb 2025 · cs.SI · 1 citations (OpenAlex)
arXiv:2502.01810 · PDF · DOI · OpenAlex · Extracted main text
Exponential random graph models (ERGMs) are very flexible for modeling network formation but pose difficult estimation challenges due to their intractable normalizing constant. Existing methods, such as MCMC-MLE, rely on sequential simulation at every optimization step. We propose a neural network approach that trains on a single, large set of parameter-simulation pairs to learn the mapping from parameters to average network statistics. Once trained, this map can be inverted, yielding a fast and parallelizable estimation method. The procedure also accommodates extra network statistics to mitigate model misspecification. Some simple illustrative examples show that the method performs well in practice.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Mele (2017) `A structural model of dense network formation', Econometrica 85(3), 825–850 self | 0.737 | 3 | 2 | 100% |
| 2 | Chatterjee \ Diaconis (2013) `Estimating and understanding exponential random graph models', The Annals of Statistics 41(5), 2428 – 2461 | 0.644 | 2 | 2 | 100% |
| 3 | Wei \ Jiang `Estimating parameters of structural models using neural networks', Marketing Science | 0.644 | 2 | 2 | 100% |
| 4 | Bhamidi, Bresler \ Sly (2011) `Mixing time of exponential random graphs', The Annals of Applied Probability 21(6), 2146–2170 | 0.405 | 1 | 1 | 100% |
| 5 | Boucher \ Mourifie (2017) `My friend far far away: A random field approach to exponential random graph models', Econometrics Journal 20(3), S14–S46 | 0.405 | 1 | 1 | 100% |
| 6 | Caimo \ Friel (2010) `Bayesian inference for exponential random graph models', Social Networks | 0.405 | 1 | 1 | 100% |
| 7 | DePaula (2017) Econometrics of network models, in B.Honore, A.Pakes, M.Piazzesi \ L.Samuelson, eds, `Advances in Economics and Econometrics: El… | 0.405 | 1 | 1 | 100% |
| 8 | DePaula, Richards-Shubik \ Tamer (2018) `Identifying preferences in networks with bounded degree', Econometrica 86(1), 263–288 | 0.405 | 1 | 1 | 100% |
| 9 | Geyer \ Thompson (1992) `Constrained monte carlo maximum likelihood for depedendent data', Journal of the Royal Statistical Society, Series B (Methodolo… | 0.405 | 1 | 1 | 100% |
| 10 | Graham (2017) `An empirical model of network formation: with degree heterogeneity', Econometrica 85(4), 1033–1063 | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 17 scored citations.