مؤتمر
Estimation of confidence regions for random excursion sets with application to large-scale ice-sheet simulations
| العنوان: | Estimation of confidence regions for random excursion sets with application to large-scale ice-sheet simulations Estimation de régions de confiance pour des ensembles aléatoires avec application à des simulations glaciologiques à grande échelle |
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| المؤلفون: | Bulthuis, Kevin, Pattyn, Frank, Arnst, Maarten |
| المساهمون: | F.R.S.-FNRS - Fonds de la Recherche Scientifique, sponsor |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | uncertainty quantification, confidence regions, ice sheet simulations, Engineering, computing & technology :: Mechanical engineering, Ingénierie, informatique & technologie :: Ingénierie mécanique |
| جغرافية الموضوع: | international |
| الوصف: | In many applications, including in evaluations of failure regions and in geophysical hazard assessment, weare interested in evaluating excursion sets, that is, regions in the spatial domain where the response functionexceeds some critical value. Determining such excursion sets in the presence of uncertainties in a model isan interesting problem connected with the theory of random sets. A first issue connected with random excursion sets is in defining confidence regions that can properlyrepresent the uncertainty in the excursion sets . Here, we adopt a definition based on a generalization of theconcept of confidence regions based on previous works by [Bolin, 2015] and [French, 2015]. An outer orinner confidence region is defined as a region that contains or is contained in the excursion set with a givenlevel of probability, respectively.Such confidence regions are approximated numerically as optimal subsets within a parametric family ofsubsets with the appropriate coverage probability, which provides nested approximations for the confidenceregions. A second issue, related to this numerical approximation of confidence regions, stems from thenumerical approximation of the coverage probability, which may prove challenging for computationallyintensive models and small probability levels. Here, we explore methods based on a hybrid surrogate-basedapproach [Li, 2010] and subset simulation [Au, 2001] to evaluate the coverage probability.We apply this methodology to the evaluation of confidence regions for the retreat of grounded ice in largescale simulation of the Antarctic ice sheet subject to parametric uncertainties. [1] [Au, 2001] Au, S.-K. and Beck, J. L. (2001). Estimation of small failure probabilities in high dimensionsby subset simulation. Probabilistic Engineering Mechanics, 16(4):263–277.[2] [Bolin, 2015] Bolin, D. and Lindgren, F. (2015). Excursion and contour uncertainty regions for latentgaussian models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 77(1):85–106.[3] [French, 2015] French, J. P. and Hoeting, J. A. (2015). Credible regions for exceedance sets ofgeostatistical data. Environmetrics, 27(1):4–14.[4] [Li, 2010] Li, J. and Xiu, D. (2010). Evaluation of failure probability via surrogate models. Journal ofComputational Physics, 229(23):8966–8980. |
| نوع الوثيقة: | conferencePaper |
| اللغة: | English |
| Relation: | UNCECOMP 2019: 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Hersonissos, Greece (24-26 June 2019) |
| URL الوصول: | https://orbi.uliege.be/handle/2268/238637 |
| حقوق: | info:eu-repo/semantics/openAccess |
| رقم الأكسشن: | edsorb.238637 |
| قاعدة البيانات: | ORBi |
| الوصف غير متاح. |