Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty. Uncertainty analysis aims to quantify the overall uncertainty within a model, in order to support problem owners in model-based decision-making. In recent years there has been an explosion of interest in uncertainty analysis. Uncertainty and dependence elicitation, dependence modelling, model inference, efficient sampling, screening and sensitivity analysis, and probabilistic inversion are among the active research areas. This text provides both the mathematical foundations and practical applications in this rapidly expanding area, including:
Uncertainty Analysis with High Dimensional Dependence Modelling offers a comprehensive exploration of a new emerging field. It will prove an invaluable text for researches, practitioners and graduate students in areas ranging from statistics and engineering to reliability and environmetrics.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Dorota Kurowicka and Roger M. Cooke are the authors of Uncertainty Analysis with High Dimensional Dependence Modelling, published by Wiley.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : New. Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty. Series: Wiley Series in Probability and Statistics. Num Pages: 302 pages, Illustrations (some col.). BIC Classification: PB. Category: (P) Professional & Vocational. Dimension: 233 x 180 x 22. Weight in Grams: 568. . 2006. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9780470863060
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