Model discrepancy calibration across experimental settings

Kathryn A. Maupin and Laura P. Swiler

Reliability Engineering and System Safety, 2020, vol. 200, issue C

Abstract: Despite continuing advances in the reliability of computational modeling and simulation, model inadequacy remains a pervasive concern across scientific disciplines. Further challenges are introduced into the already complex problem of “correcting†an inadequate model when experimental data is collected at varying experimental settings. This paper introduces a general approach to calibrating a model discrepancy function when the model is expected to perform for multiple experimental configurations and give predictions as a function of temporal and/or spatial coordinates.

Keywords: Computational modeling; Model inadequacy; Model form error; Model discrepancy; Inverse problems; Bayes’ Rule (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:200:y:2020:i:c:s0951832019301802

DOI: 10.1016/j.ress.2020.106818

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