Statistical calibration of computer simulations

Katherine Campbell

Reliability Engineering and System Safety, 2006, vol. 91, issue 10, 1358-1363

Abstract: This paper surveys issues associated with the statistical calibration of physics-based computer simulators. Even in solidly physics-based models there are usually a number of parameters that are suitable targets for calibration. Statistical calibration means refining the prior distributions of such uncertain parameters based on matching some simulation outputs with data, as opposed to the practice of “tuning†or point estimation that is commonly called calibration in non-statistical contexts. Older methods for statistical calibration are reviewed before turning to recent work in which the calibration problem is embedded in a Gaussian process model. In procedures of this type, parameter estimation is carried out simultaneously with the estimation of the relationship between the calibrated simulator and truth.

Keywords: Calibration; Simulation; Prediction errors; Calibrated prediction; Uncertainty analysis; Bayesian model calibration; Statistical emulation; Generalized likelihood uncertainty estimation; Regional sensitivity analysis (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:91:y:2006:i:10:p:1358-1363

DOI: 10.1016/j.ress.2005.11.032

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