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Academic & Professional Books  Reference  Data Analysis & Modelling  Data Analysis & Statistics

Sensitivity Analysis in Practice A Guide to Assessing Scientific Models

By: Andrea Saltelli(Author), Stefano Tarantola(Author), Francesca Campolongo(Author), Marco Ratto(Author)
Sensitivity Analysis in Practice
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  • Sensitivity Analysis in Practice ISBN: 9780470870938 Hardback Feb 2004 Usually dispatched within 5 days
    £71.75
    #160266
Price: £71.75
About this book Contents Customer reviews Related titles

About this book

Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. Sensitivity Analysis in Practice guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB – a widely distributed freely-available sensitivity analysis software package developed by the authors – for solving problems in sensitivity analysis of statistical models.

Contents

Chapter 1 A Worked Example
Chapter 2 Global Sensitivity Analysis for Importance Assessment
Chapter 3 Test Cases
Chapter 4 The Screening Exercise
Chapter 5 Methods Based on Decomposing the Variance of the Output
Chapter 6 Sensitivity Analysis in Diagnostic Modelling: Monte Carlo Filtering and Regionalised Sensitivity Analysis; Bayesian Uncertainty Estimation and Global Sensitivity Analysis
Chapter 7 How to Use Simlab
Chapter 8 Famous Quotes: Sensitivity Analysis in the Scientific Discourse

Customer Reviews

By: Andrea Saltelli(Author), Stefano Tarantola(Author), Francesca Campolongo(Author), Marco Ratto(Author)
Media reviews

"[...] an interesting and informative book [...] "
Technometrics, May 2005

"[...] provides an accessible overview of the most widely used sensitivity analysis methods."
Zentralblatt Math, Vol.1049, 2004

"[...] well written[...]"
Statistical Methods in Medical Research, Vol. 14, 2005

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