Sensitivity Analysis in Practice: A Guide to Assessing Scientific ModelsJohn Wiley & Sons, 16 lug 2004 - 232 pagine 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. This book 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. Other key features:
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Sommario
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2 GLOBAL SENSITIVITY ANALYSIS FOR IMPORTANCE ASSESSMENT | 31 |
3 TEST CASES | 63 |
4 THE SCREENING EXERCISE | 91 |
5 METHODS BASED ON DECOMPOSING THE VARIANCE OF THE OUTPUT | 109 |
6 SENSITIVITY ANALYSIS IN DIAGNOSTIC MODELLING MONTE CARLO FILTERING AND REGIONALISED SENSITIVITY ANALYSIS B... | 151 |
7 HOW TO USE SIMLAB | 193 |
8 FAMOUS QUOTES SENSITIVITY ANALYSIS IN THE SCIENTIFIC DISCOURSE | 205 |
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Altre edizioni - Visualizza tutto
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models A. Saltelli,Stefano Tarantola,Francesca Campolongo,Marco Ratto Anteprima non disponibile - 2004 |
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models A. Saltelli Anteprima non disponibile - 2004 |
Parole e frasi comuni
anchovies behaviour bungee jumping Campolongo Chapter coefficient of determination computed conditional variances correlation decomposition defined elementary effects Equation example factor Xi Figure first-order effects first-order indices first-order sensitivity fixed geosphere geosphere layer given global sensitivity analysis hedging hmin identify implies input factors interaction structure larvae Level E model likelihood function linear main effect marginal distributions matrix mean method of Morris model evaluations model output model parameters Monte Carlo filtering Morris method non-linear non-monotonic non-orthogonal input number of model number of portfolio obtained orthogonal inputs output variance performed portfolio model portfolio revisions prior distribution problem quantitative r-LHS Ratto Retention factor risk Saltelli sample scatter plots Scientific Models selected sensitivity indices sensitivity measure Setting FP SIMLAB simulation Smirnov test Sobol subset Table Tarantola tion uncertainty analysis variables variance based methods variance decomposition variance-based vector weighting function