- Series: Wiley Series in Probability and Statistics (Book 535)
- Hardcover: 475 pages
- Publisher: Wiley; 1 edition (October 15, 2000)
- Language: English
- ISBN-10: 0471998923
- ISBN-13: 978-0471998921
- Product Dimensions: 6.8 x 1.3 x 9.7 inches
- Shipping Weight: 2.3 pounds (View shipping rates and policies)
- Average Customer Review: 3 customer reviews
- Amazon Best Sellers Rank: #229,305 in Books (See Top 100 in Books)
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Sensitivity Analysis 1st Edition
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"The book has a fair price...I think this is a book that everyonewho does modeling should buy. It can readily be read piecemeal...soit is ideal for leisurely self-study..." (Technometrics Vol. 42,No. 4 May 2001)
"...this book will prove helpful in the solution of many modelingproblems." (La Doc Sti, September 2000)
"...presents many different sensitivity analysis methodologies anddemonstrates their usefulness in scientific research."(Zentralblatt MATH, Vol. 961, 2001/11)
From the Back Cover
Sensitivity analysis is used to ascertain how a given model outputdepends upon the inupt parameters. This is an important method forchecking the quality of a given model, as well as a powerful toolfor checking the robustness and reliability of its analysis. Thetopic is acknowledged as essential for good modelling practice, andis an implicit part of any modelling field.
* Offers an accessible introduction to sensitivity analysis
* Covers all the latest research
* Illustrates concepts with numerous examples, applications andcase studies
* Includes contributions from the leading researchers active indeveloping strategies for sensitivity analysis
The principles of sensitivity analysis are carefully described, andsuitable methods for approaching many types of problems are given.The book introduces the modeller to the entire casual assessmentchain, from data to predictions, whilst explaining the impact ofsource uncertainties and framing assumptions. A 'hitch-hiker'sguide' is included to allow the more experienced reader to readilyaccess specific applications.
Modellers from a wide range of disciplines, includingbiostatistics, economics, environmental impact assessment,chemistry and engineering will benefit greatly from the numerousexamples and applications.
Top customer reviews
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Although this is a multi-authored book, the discourse flows clearly across (most of) the chapters and coveys the main element of this new discipline.
The authors-editors show an overall preference for sensitivity analysis methods capable of global quantitative sensitivity analysis; the sections of the book devoted to local methods and to regression analysis are rather a useful review than actually new material. The sections on variance-based methods and on high dimensional model representations are probably the most instructive for the educated reader.
The applications are in general well presented and instructive. These range from atmospheric chemistry to material physics. A chapter on available software is also offered. Finally the chapter from Beck and Chen (Assuring The Quality Of Models Designed For Predictive Tasks) establishes the needed link between the present raging debate on model validation and the use of adequate sensitivity analysis methods.
The book is highly recommendable to all researchers involved in modeling in a very broad range of complex systems, such as in economy, environmental studies, biology, medical engineering, chemistry etc.