Sensitivity Analysis

Gauging the Worth of Scientific Models

By: Andrea Saltelli (Editor), K. Chan (Editor), E. M. Scott (Editor)

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Hardcover | 15 September 2000 | Edition Number 1

At a Glance

Hardcover
512 Pages

Dimensions(cm)
24.62 x 17.45 x 3.32

Hardcover

RRP $313.45

$312.75

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Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters. This is an important method for checking the quality of a given model, as well as a powerful tool for checking the robustness and reliability of its analysis. The topic is acknowledged as essential for good modelling practice, and is 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 and case studies ? Includes contributions form the leading researchers active in developing strategies for sensitivity analysis The principles of sensitivity analysis area carefully described, and suitable methods for approaching many types of problems are given. The book introduces the modeller to the entire causal assessment chain, from data to predictions, whilst explaining the impact of source uncertainties and framing assumptions. A 'hitch-hiker's guide' is included to allow the more experienced reader to readily access specific applications. Modellers from a wide range of disciplines, including biostatistics, economics, environmental impact assessment, chemistry and engineering will benefit greatly form the numerous examples and applications.

Industry Reviews

"The book has a fair price...I think this is a book that everyone who does modeling should buy. It can readily be read piecemeal...so it is ideal for leisurely self-study..." (Technometrics Vol. 42, No. 4 May 2001)
"...this book will prove helpful in the solution of many modeling problems." (La Doc Sti, September 2000)
"...presents many different sensitivity analysis methodologies and demonstrates their usefulness in scientific research." (Zentralblatt MATH, Vol. 961, 2001/11)

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