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Bayesian Calibration of Inexact Computer Models

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  • Matthew Plumlee

Abstract

Bayesian calibration is used to study computer models in the presence of both a calibration parameter and model bias. The parameter in the predominant methodology is left undefined. This results in an issue, where the posterior of the parameter is suboptimally broad. There has been no generally accepted alternatives to date. This article proposes using Bayesian calibration, where the prior distribution on the bias is orthogonal to the gradient of the computer model. Problems associated with Bayesian calibration are shown to be mitigated through analytic results in addition to examples. Supplementary materials for this article are available online.

Suggested Citation

  • Matthew Plumlee, 2017. "Bayesian Calibration of Inexact Computer Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1274-1285, July.
    • Handle: RePEc:taf:jnlasa:v:112:y:2017:i:519:p:1274-1285
    DOI: 10.1080/01621459.2016.1211016
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    References listed on IDEAS

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    1. Matthew Plumlee & V. Roshan Joseph & Hui Yang, 2016. "Calibrating Functional Parameters in the Ion Channel Models of Cardiac Cells," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 500-509, April.
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    Cited by:

    1. Jun Yuan & Haowei Wang & Szu Hui Ng & Victor Nian, 2020. "Ship Emission Mitigation Strategies Choice Under Uncertainty," Energies, MDPI, vol. 13(9), pages 1-20, May.
    2. Maupin, Kathryn A. & Swiler, Laura P., 2020. "Model discrepancy calibration across experimental settings," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    3. Wang, Bo & Zhang, Qiong & Xie, Wei, 2019. "Bayesian sequential data collection for stochastic simulation calibration," European Journal of Operational Research, Elsevier, vol. 277(1), pages 300-316.
    4. Na, Wei & Wang, Mingming, 2022. "A Bayesian approach with urban-scale energy model to calibrate building energy consumption for space heating: A case study of application in Beijing," Energy, Elsevier, vol. 247(C).

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