Sensitivity analysis / edited by Andrea Saltelli, Karen Chan, E. Marian Scott.

Format:

Book

Contributor:

Saltelli, A. (Andrea), 1953-

Chan, K. (Karen)

Scott, E. M. (E. Marian)

Series:

Wiley series in probability and statistics

Language:

English

Subjects (All):

Sensitivity theory (Mathematics)--Statistical methods.

Sensitivity theory (Mathematics).

Statistics.

Physical Description:

xv, 475 pages : illustrations ; cm.

Place of Publication:

Chichester ; New York : Wiley, [2000]

Summary:

Modellers from a wide range of disciplines, including biostatistics, economics, environmental impact assessment, chemistry and engineering will benefit greatly form the numerous examples and applications.

Contents:

1 What is Sensitivity Analysis 3

1.2 An example 4

1.3 Why carry out a sensitivity analysis 5

1.4 How to perform sensitivity analysis 7

1.5 Goals of sensitivity analysis 8

1.6 Properties of various types of sensitivity analysis techniques 10

1.7 Choice of methods 11

2 Hitchhiker's Guide to Sensitivity Analysis 15

2.2 Screening designs 17

2.3 Differential analysis 18

2.4 Monte Carlo analysis 20

2.5 Measures of importance 28

2.6 Response surface methodology 31

2.7 FORM and SORM 32

2.8 Comparing different approaches 32

2.9 Analytical test models 33

2.10 When to use what 45

Part II Methods

3 Designs of Experiments 51

3.3 Factorial designs 53

3.4 Fractional factorial designs 57

3.5 Other designs 59

3.6 DOE for computer experiments 60

3.7 More on DOE for computer experiments: the prediction problem 61

4 Screening Methods 65

4.3 One-at-a-time (OAT) designs 67

4.4 Morris's (1991) OAT designs 68

4.5 Cotter's design 73

4.6 Andres' iterated fractional factorial design (IFFD) 74

4.7 Bettonvil's sequential bifurcation 77

5 Local Methods 81

5.2 Features of local sensitivities 82

5.3 Numerical methods for the calculation of local sensitivities 83

5.4 Derived sensitivities 85

5.5 Interpretations of sensitivity information 87

5.6 Initial sensitivities 89

5.7 Functional sensitivities 91

5.8 Scaling and self-similarity relations 91

5.9 Applications of local sensitivities 93

6 Sampling-Based Methods 101

6.2 Definition of distributions for subjective uncertainty 103

6.3 Sampling procedures 106

6.4 Evaluation of model 115

6.5 Uncertainity analysis 116

6.6 Sensitivity analysis 121

7 Reliability Algorithms: FORM and SORM Methods 155

7.2 Brief review of reliability algorithms 157

7.3 A review of applications 161

7.4 Summary of recent theoretical advances 163

8 Variance-Based Methods 167

8.2 Correlation ratios/importance measures 168

8.3 Method of Sobol' 174

8.4 The FAST method 181

8.5 Sampling strategies 190

8.7 Last remarks on ANOVA decomposition 197

9 Managing the Tyranny of Parameters in Mathematical Modelling of Physical Systems 199

9.2 High-dimensional model representations 203

9.4 Applications of HDMR 216

10 Bayesian Sensitivity Analysis 225

10.1 Sensitivity analysis in Bayesian analysis: an introduction 225

10.2 Sensitivity to the prior 228

10.3 Issues in general sensitivity analysis 231

10.4 Foundational issues 233

10.5 Stability theory 234

10.6 Computation of nondominated alternatives 235

10.7 Extracting additional information 236

10.8 Maximin solutions 239

11 Graphical Methods 245

11.3 Tornado graphs 246

11.4 Radar graphs 247

11.5 Generalized reachable sets 247

11.6 Matrix and overlay scatterplots 249

11.7 Cobweb plots 251

11.8 Cobweb plots for local sensitivity: dike-ring reliability 256

11.9 Radar plots for importance: internal dosimetry 258

11.10 Scatterplots for steering of directional samples: uplifting and piping 261

Part III Applications

12 Practical Experience in Applying Sensitivity and Uncertainty Analysis 267

12.2 The modelling process 269

13 Scenario and Parametric Sensitivity and Uncertainty Analysis in Nuclear Waste Disposal Risk Assessment: The Case of GESAMAC 275

13.1 Introduction: the GESAMAC project 275

13.2 Results for the radionuclide chain 278

14 Sensitivity Analysis for Signal Extraction in Economic Time Series 293

14.2 General framework 295

14.3 Model assessment and parameter uncertainty 298

14.4 Sensitivity analysis 304

15 A Dataless Precalibration Analysis in Solid State Physics 311

15.2 Data analysis technique 312

15.3 Sensitivity analysis 313

16 Application of First-Order (FORM) and Second-Order (SORM) Reliability Methods: Analysis and Interpretation of Sensitivity Measures Related to Groundwater Pressure Decreases and Resulting Ground Subsidence 317

16.2 FORM sensitivity information 318

16.4 Results and discussion 322

17 One-at-a-Time and Mini-Global Analyses for Characterizing Model Sensitivity in the Nonlinear Ozone Predictions from the US EPA Regional Acid Deposition Model (RADM) 329

17.2 Methods and experimental design 332

17.3 Results 338

18 Comparing Different Sensitivity Analysis Methods on a Chemical Reactions Model 355

18.2 Local OAT Approaches: the EOAT and the derivative-based designs 355

18.3 The KIM model 356

18.4 Comparing different SA approaches on KIM 359

18.5 A quantitative SA analysis 361

19 An Application of Sensitivity Analysis to Fish Population Dynamics 367

19.2 General characteristics of pelagic fish assemblages analyzed 368

19.3 A stage-based modelling approach to analyze fluctuations in pelagic fish populations 371

19.4 Sensitivity analysis by the Morris method 378

20 Global Sensitivity Analysis: A Quality Assurance Tool in Environmental Policy Modelling 385

20.2 Why sensitivity analysis? 386

20.3 Model structure and uncertainties 387

20.4 Data availability 388

20.5 Computing air emissions 388

20.6 Pressure indicators 389

20.7 Indicators of total burden 391

20.8 Pressure-to-decision indices 391

20.9 Results and discussion 393

21 Assuring the Quality of Models Designed for Predictive Tasks 401

21.2 The impasse 403

21.3 A regionalized sensitivity analysis 407

21.4 Assessing the quality of a model for predictive exposure assessments 412

21.5 Challenging high-level conceptual insights 417

22 Fortune and Future of Sensitivity Analysis 421

22.1 Introduction: sensitivity analysis as an ingredient of modelling 421

22.2 The fortune 422

22.3 The future 424

Software for Sensitivity Analysis

A Brief Review 451

A.2 Software for Sensitivity Analysis 451

A.3 Other Sensitivity Analysis Software 459

A.4 Generic Algorithms 462.

Notes:

Includes bibliographical references (pages [427]-447) and index.

ISBN:

0471998923

OCLC:

43552650