Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 91, Issue 10-11, Pages 1358-1363Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2005.11.032
Keywords
calibration; simulation; prediction errors; calibrated prediction; uncertainty analysis; Bayesian model calibration; statistical emulation; generalized likelihood uncertainty estimation; regional sensitivity analysis
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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. (c) 2005 Elsevier Ltd. All rights reserved.
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