Open Access
2021 Estimation of a density using an improved surrogate model
Michael Kohler, Adam Krzyżak
Electron. J. Statist. 15(1): 650-690 (2021). DOI: 10.1214/20-EJS1774


Quantification of uncertainty of a technical system is often based on a surrogate model of a corresponding simulation model. In any application the simulation model will not describe the reality perfectly, and consequently also the surrogate model will be imperfect. In this article we show how observed data of the real technical system can be used to improve such a surrogate model, and we analyze the rate of convergence of density estimates based on the improved surrogate model. The results are illustrated by applying the estimates to simulated and real data.


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Michael Kohler. Adam Krzyżak. "Estimation of a density using an improved surrogate model." Electron. J. Statist. 15 (1) 650 - 690, 2021.


Received: 1 September 2019; Published: 2021
First available in Project Euclid: 19 January 2021

Digital Object Identifier: 10.1214/20-EJS1774

Primary: 62G07
Secondary: 62P30

Keywords: $L_{1}$ error , Density estimation , imperfect models , surrogate models , uncertainty quantification

Vol.15 • No. 1 • 2021
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