A D-Optimal Sequential Calibration Design for Computer Models

Huaimin Diao, Yan Wang and Dianpeng Wang
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Huaimin Diao: School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China
Yan Wang: School of Statistics and Data Science, Beijing University of Technology, Beijing 100124, China
Dianpeng Wang: School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China

Mathematics, 2022, vol. 10, issue 9, 1-15

Abstract: The problem with computer model calibration by tuning the parameters associated with computer models is significant in many engineering and scientific applications. Although several methods have been established to estimate the calibration parameters, research focusing on the design of calibration parameters remains limited. Therefore, this paper proposes a sequential computer experiment design based on the D-optimal criterion, which can efficiently tune the calibration parameters while improving the prediction ability of the calibrated computer model. Numerical comparisons of the simulated and real data demonstrate the efficiency of the proposed technique.

Keywords: calibration; computer models; fisher information; sequential D-optimal; surrogate model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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