Sensitivity Analysis in Practice A Guide to Assessing Scientific Models

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

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