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Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates

Barde, Sylvain (2024) Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates. Computational Statistics & Data Analysis, 196 . Article Number 107972. ISSN 0167-9473. E-ISSN 1872-7352. (In press) (doi:10.1016/j.csda.2024.107972) (KAR id:105736)


Large scale, computationally expensive simulation models pose a particular challenge when it comes to estimating their parameters from empirical data. Most simulation models do not possess closed-form expressions for their likelihood function, requiring the use of simulation-based inference, such as simulated method of moments, indirect inference, likelihood-free inference or approximate Bayesian computation. However, given the high computational requirements of large-scale models, it is often difficult to run these estimation methods, as they require more simulated runs that can feasibly be carried out. The aim is to address the problem by providing a full Bayesian estimation framework where the true but intractable likelihood function of the simulation model is replaced by one generated by a surrogate model trained on the limited simulated data. This is provided by a Linear Coregionalization Model, where each latent variable is a sparse variational Gaussian process, chosen for its desirable convergence and consistency properties. The effectiveness of the approach is tested using both a simulated Bayesian computing analysis on a known data generating process, and an empirical application in which the free parameters of a computationally demanding agent-based model are estimated on US macroeconomic data.

Item Type: Article
DOI/Identification number: 10.1016/j.csda.2024.107972
Uncontrolled keywords: linear model of coregionalization; likelihood-free inference; variational inference; agent-based model; non-parametric method
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
Divisions: Divisions > Division of Human and Social Sciences > School of Economics
Funders: University of Kent (
Depositing User: Sylvain Barde
Date Deposited: 25 Apr 2024 08:38 UTC
Last Modified: 26 Apr 2024 09:01 UTC
Resource URI: (The current URI for this page, for reference purposes)

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