Sensitivity analysis in practice: A guide to assessing scientific models
Saltelli, A; Tarantola, S; Campolongo, F; Ratto, M
HERO ID
1065451
Reference Type
Book/Book Chapter
Year
2004
Language
English
| HERO ID | 1065451 |
|---|---|
| Year | 2004 |
| Title | Sensitivity analysis in practice: A guide to assessing scientific models |
| Authors | Saltelli, A; Tarantola, S; Campolongo, F; Ratto, M |
| Publisher Text | John Wiley & Sons |
| City | West Sussex, UK |
| Abstract | This book is a ‘primer’ in global sensitivity analysis (SA). Its ambition is to enable the reader to apply global SA to a mathematical or computational model. It offers a description of a few selected techniques for sensitivity analysis, used for assessing the relative importance of model input factors. These techniques will answer questions of the type ‘which of the uncertain input factors is more important in determining the uncertainty in the output of interest?’ or ‘if we could eliminate the uncertainty in one of the input factors, which factor should we choose to reduce the most the variance of the output?’ Throughout this primer, the input factors of interest will be those that are uncertain, i.e. whose value lie within a finite interval of non-zero width. As a result, the reader will not find sensitivity analysis methods here that look at the local property of the input–output relationships, such as derivative-based analysis. Special attention is paid to the selection of the method, to the framing of the analysis and to the interpretation and presentation of the results. The examples will help the reader to apply the methods in a way that is unambiguous and justifiable, so as to make the sensitivity analysis an added value to model-based studies or assessments. Both diagnostic and prognostic uses of models will be considered (a description of these is in Chapter 2), and Bayesian tools of analysis will be applied in conjunction with sensitivity analysis. When discussing sensitivity with respect to factors, we shall interpret the term ‘factor’ in a very broad sense: a factor is anything that can be changed in a model prior to its execution. This also includes structural or epistemic sources of uncertainty. To make an example, factors will be presented in applications that are in fact ‘triggers’, used to select one model structure versus another, one mesh size versus another, or altogether different conceptualisations of a system. |
| Doi | 10.1002/0470870958 |
| Is Certified Translation | No |
| Dupe Override | No |
| Isbn | 0-470-87093-1 |
| Is Public | Yes |
| Language Text | English |