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[null,"1.","Record Nr.",null,"UNINA9911019911203321"]
[null,null,"Titolo",null,"Sensitivity analysis in practice : a guide to assessing scientific models / / Andrea Saltelli ... [et al.]"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, NJ, : Wiley, c2004"]
[null,null,"ISBN",null,"9786610539789"]
[{"$nulls":4},"9781280539787"]
[{"$nulls":4},"128053978X"]
[{"$nulls":4},"9780470870945"]
[{"$nulls":4},"047087094X"]
[{"$nulls":4},"9780470870952"]
[{"$nulls":4},"0470870958"]
[null,null,"Descrizione fisica",null,"1 online resource (233 p.)"]
[null,null,"Disciplina",null,"003/.5"]
[null,null,"Soggetti",null,"Sensitivity theory (Mathematics) - Simulation methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. [211]-216) and index."]
[null,null,"Nota di contenuto",null,"SENSITIVITY ANALYSIS IN PRACTICE; CONTENTS; PREFACE; 1 A WORKED EXAMPLE; 1.1 A simple model; 1.2 Modulus version of the simple model; 1.3 Six-factor version of the simple model; 1.4 The simple model 'by groups'; 1.5 The (less) simple correlated-input model; 1.6 Conclusions; 2 GLOBAL SENSITIVITY ANALYSIS FOR IMPORTANCE ASSESSMENT; 2.1 Examples at a glance; 2.2 What is sensitivity analysis?; 2.3 Properties of an ideal sensitivity analysis method; 2.4 Defensible settings for sensitivity analysis; 2.5 Caveats; 3 TEST CASES; 3.1 The jumping man. Applying variance-based methods"]
[{"$nulls":4},"3.2 Handling the risk of a financial portfolio: the problem of hedging. Applying Monte Carlo filtering and variance-based methods3.3 A model of fish population dynamics. Applying the method of Morris; 3.4 The Level E model. Radionuclide migration in the geosphere. Applying variance-based methods and Monte Carlo filtering; 3.5 Two spheres. Applying variance based methods in estimation/calibration problems; 3.6 A chemical experiment. Applying variance based methods in estimation/calibration problems; 3.7 An analytical example. Applying the method of Morris; 4 THE SCREENING EXERCISE"]
[{"$nulls":4},"4.1 Introduction4.2 The method of Morris; 4.3 Implementing the method; 4.4 Putting the method to work: an analytical example; 4.5 "]
[{"$nulls":4},"Putting the method to work: sensitivity analysis of a fish population model; 4.6 Conclusions; 5 METHODS BASED ON DECOMPOSING THE VARIANCE OF THE OUTPUT; 5.1 The settings; 5.2 Factors Prioritisation Setting; 5.3 First-order effects and interactions; 5.4 Application of S(i) to Setting 'Factors Prioritisation'; 5.5 More on variance decompositions; 5.6 Factors Fixing (FF) Setting; 5.7 Variance Cutting (VC) Setting; 5.8 Properties of the variance based methods"]
[{"$nulls":4},"5.9 How to compute the sensitivity indices: the case of orthogonal input5.9.1 A digression on the Fourier Amplitude Sensitivity Test (FAST); 5.10 How to compute the sensitivity indices: the case of non-orthogonal input; 5.11 Putting the method to work: the Level E model; 5.11.1 Case of orthogonal input factors; 5.11.2 Case of correlated input factors; 5.12 Putting the method to work: the bungee jumping model; 5.13 Caveats; 6 SENSITIVITY ANALYSIS IN DIAGNOSTIC MODELLING: MONTE CARLO FILTERING AND REGIONALISED SENSITIVITY ANALYSIS, BAYESIAN UNCERTAINTY ESTIMATION AND GLOBAL SENSITIVITY ANALYSIS"]
[{"$nulls":4},"6.1 Model calibration and Factors Mapping Setting6.2 Monte Carlo filtering and regionalised sensitivity analysis; 6.2.1 Caveats; 6.3 Putting MC filtering and RSA to work: the problem of hedging a financial portfolio; 6.4 Putting MC filtering and RSA to work: the Level E test case; 6.5 Bayesian uncertainty estimation and global sensitivity analysis; 6.5.1 Bayesian uncertainty estimation; 6.5.2 The GLUE case; 6.5.3 Using global sensitivity analysis in the Bayesian uncertainty estimation; 6.5.4 Implementation of the method; 6.6 Putting Bayesian analysis and global SA to work: two spheres"]
[{"$nulls":4},"6.7 Putting Bayesian analysis and global SA to work: a chemical experiment"]
[null,null,null,"Sommario/riassunto","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 anal"]