The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Sequential design of computer experiments for the estimation of a probability of failure
Open accessAbstract
This paper deals with the problem of estimating the volume of the excursion set of a function f:ℝd→ℝ above a given threshold, under a probability measure on ℝd that is assumed to be known. In the industrial world, this corresponds to the problem of estimating a probability of failure of a system. When only an expensive-to-simulate model of the system is available, the budget for simulations is usually severely limited and therefore classical Monte Carlo methods ought to be avoided. One of the main contributions of this article is to derive SUR (stepwise uncertainty reduction) strategies from a Bayesian formulation of the problem of estimating a probability of failure. These sequential strategies use a Gaussian process model of f and aim at performing evaluations of f as efficiently as possible to infer the value of the probability of failure. We compare these strategies to other strategies also based on a Gaussian process model for estimating a probability of failure.
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Citations
Cites
Efficient Global Optimization of Expensive Black-Box Functions
Jones, D. R., Schonlau, M., & Welch, W. J. (1998) · Journal of Global Optimization · doi:10.1023/a:1008306431147 · Cited by 8,070
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
Cited by
The frontier of simulation-based inference
Cranmer, K., Brehmer, J., & Louppe, G. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1912789117 · Cited by 1,032
POLYNOMIAL-CHAOS-BASED KRIGING
Schobi, R., Sudret, B., & Wiart, J. (2015) · International Journal for Uncertainty Quantification · doi:10.1615/int.j.uncertaintyquantification.2015012467 · Cited by 398
Metadata
- Authors
- Bect, J., Ginsbourger, D., Li, L., Picheny, V., & Vazquez, E.
- Venue
- Statistics and Computing
- Published
- 2011-04-21
- Volume
- 22
- Issue
- 3
- Pages
- 773-793
- ISSN
- 0960-3174 (ISSN-L)
- 1573-1375
- OpenAlex
- W2133118715
- Cited by
- 321
- References
- 2
- FWCI
- 12.12
- Type
- journal article
- Language
- en
- Open access
- green
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- Bect, J., Ginsbourger, D., Li, L., Picheny, V., & Vazquez, E. (2012). Sequential design of computer experiments for the estimation of a probability of failure. Statistics and Computing. https://doi.org/10.1007/s11222-011-9241-4
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
