Uncertainty Analysis with High Dimensional Dependence Modelling

This book PDF is perfect for those who love Mathematics genre, written by Dorota Kurowicka and published by John Wiley & Sons which was released on 02 October 2006 with total hardcover pages 302. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Uncertainty Analysis with High Dimensional Dependence Modelling books below.

Uncertainty Analysis with High Dimensional Dependence Modelling
Author : Dorota Kurowicka
File Size : 42,9 Mb
Publisher : John Wiley & Sons
Language : English
Release Date : 02 October 2006
ISBN : 9780470863084
Pages : 302 pages
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Uncertainty Analysis with High Dimensional Dependence Modelling by Dorota Kurowicka Book PDF Summary

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: An up-to-date, comprehensive overview of the foundations and applications of uncertainty analysis. All the key topics, including uncertainty elicitation, dependence modelling, sensitivity analysis and probabilistic inversion. Numerous worked examples and applications. Workbook problems, enabling use for teaching. Software support for the examples, using UNICORN - a Windows-based uncertainty modelling package developed by the authors. A website featuring a version of the UNICORN software tailored specifically for the book, as well as computer programs and data sets to support the examples. 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.

Uncertainty Analysis with High Dimensional Dependence Modelling

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

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