The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Framework for Validation of Computer Models
Abstract
We present a framework that enables computer model evaluation oriented toward answering the question: Does the computer model adequately represent reality? The proposed validation framework is a six-step procedure based on Bayesian and likelihood methodology. The Bayesian methodology is particularly well suited to treating the major issues associated with the validation process: quantifying multiple sources of error and uncertainty in computer models, combining multiple sources of information, and updating validation assessments as new information is acquired. Moreover, it allows inferential statements to be made about predictive error associated with model predictions in untested situations. The framework is implemented in a test bed example of resistance spot welding, to provide context for each of the six steps in the proposed validation process.
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Cites
Bayesian calibration of computer models
Kennedy, M. C., & O'Hagan, A. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00294 · Cited by 4,222
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Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China
Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., & Yang, H. (2008) · Journal of Hydrology · doi:10.1016/j.jhydrol.2008.05.012 · Cited by 800
Measures of agreement between computation and experiment: Validation metrics
Oberkampf, W. L., & Barone, M. F. (2006) · Journal of Computational Physics · doi:10.1016/j.jcp.2006.03.037 · Cited by 494
RECURSIVE CO-KRIGING MODEL FOR DESIGN OF COMPUTER EXPERIMENTS WITH MULTIPLE LEVELS OF FIDELITY
Le Gratiet, L., & Garnier, J. (2014) · International Journal for Uncertainty Quantification · doi:10.1615/int.j.uncertaintyquantification.2014006914 · Cited by 388
Perspectives on the integration between first-principles and data-driven modeling
Bradley, W., Kim, J., Kilwein, Z., Blakely, L., Eydenberg, M., Jalvin, J., Laird, C., & Boukouvala, F. (2022) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2022.107898 · Cited by 231
Metadata
- Authors
- Bayarri, M. J., Berger, J. O., Paulo, R., Sacks, J., Cafeo, J. A., Cavendish, J., Lin, C.-H., & Tu, J.
- Venue
- Technometrics
- Publisher
- Informa UK Limited
- Published
- 2007-05
- Volume
- 49
- Issue
- 2
- Pages
- 138-154
- ISSN
- 0040-1706 (ISSN-L)
- 1537-2723
- OpenAlex
- W2027319489
- Cited by
- 655
- References
- 1
- FWCI
- 26.11
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bayarri, M. J., Berger, J. O., Paulo, R., Sacks, J., Cafeo, J. A., Cavendish, J., Lin, C.-H., & Tu, J. (2007). A Framework for Validation of Computer Models. Technometrics. https://doi.org/10.1198/004017007000000092
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