Uncertainty Analysis with High Dimensional Dependence Modelling
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Beschreibung
Mathematical models are used to simulate complex real-worldphenomena in many areas of science and technology. Large complexmodels typically require inputs whose values are not known withcertainty. Uncertainty analysis aims to quantify the overalluncertainty within a model, in order to support problem owners inmodel-based decision-making. In recent years there has been anexplosion of interest in uncertainty analysis. Uncertainty anddependence elicitation, dependence modelling, model inference,efficient sampling, screening and sensitivity analysis, andprobabilistic inversion are among the active research areas. Thistext provides both the mathematical foundations and practicalapplications in this rapidly expanding area, including:
* An up-to-date, comprehensive overview of the foundations andapplications of uncertainty analysis.
* All the key topics, including uncertainty elicitation,dependence modelling, sensitivity analysis and probabilisticinversion.
* Numerous worked examples and applications.
* Workbook problems, enabling use for teaching.
* Software support for the examples, using UNICORN - aWindows-based uncertainty modelling package developed by theauthors.
* A website featuring a version of the UNICORN software tailoredspecifically for the book, as well as computer programs and datasets to support the examples.
Uncertainty Analysis with High Dimensional DependenceModelling offers a comprehensive exploration of a new emergingfield. It will prove an invaluable text for researches,practitioners and graduate students in areas ranging fromstatistics and engineering to reliability and environmetrics.
Autor*in
Dorota Kurowicka
Themen in »Uncertainty Analysis with High Dimensional Dependence Modelling«
Engineering Statistics Mathematical Modeling Mathematics Mathematik Mathematische Modellierung Statistics Statistik Statistik in den Ingenieurwissenschaften
Stimmen zu »Uncertainty Analysis with High Dimensional Dependence Modelling«
"...an invaluable reference for researchers, practitioners andgraduate students in several areas of statistics, engineering andtechnology." (Mathematical Reviews, 2007b)
"...whether one is a researcher, student, or an industrialpractitioner dealing with computer models the book comes highlyrecommended." (Technometrics, February 2007)
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