Sensitivity Analysis

Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters. This is an important method for checking the quality of a given model, as well as a powerful tool for checking the robustness and reliability of its analysis.

Zusatztext "...this book will prove helpful in the solution of many modeling problems." (La Doc Sti! September 2000)"...presents many different sensitivity analysis methodologies and demonstrates their usefulness in scientific research." (Zentralblatt MATH! Vol. 961! 2001/11) Informationen zum Autor Andrea Saltelli, Joint Research Centre of the European Commission, Ispra, Unit of Applied Statistics and Econometrics. Presently leading the Econometric and Applied Statistics Unit of the Joint Research Centre, lead author Professor Saltelli has published many articles in numerous journals over the last 30 years. He is also the main author and main editor of two previous books (both for Wiley). Klappentext Mit Hilfe einer Sensitivitätsanalyse kann man feststellen, wie ein gegebenes Modell von den Eingabeparametern abhängt und unter welchen Umständen es instabil werden könnte. Die gute Modellierungspraxis kommt ohne solche Betrachtungen zukünftig nicht mehr aus! Ausgehend von einer Erläuterung der Grundprinzipien hilft Ihnen dieses Buch, eine Lösung für Ihre Modellierungsprobleme zu finden. Die Auswirkungen von Unsicherheiten oder Annahmen werden dabei besser durchschaubar. Zusammenfassung Mit Hilfe einer Sensitivitätsanalyse kann man feststellen, wie ein gegebenes Modell von den Eingabeparametern abhängt und unter welchen Umständen es instabil werden könnte. Die gute Modellierungspraxis kommt ohne solche Betrachtungen zukünftig nicht mehr aus! Ausgehend von einer Erläuterung der Grundprinzipien hilft Ihnen dieses Buch, eine Lösung für Ihre Modellierungsprobleme zu finden. Die Auswirkungen von Unsicherheiten oder Annahmen werden dabei besser durchschaubar. Inhaltsverzeichnis What is Sensitivity Analysis.Hitchhiker's Guide to Sensitivity Analysis.METHODS.Designs of Experiments.Screening Methods.Local Methods.Sampling-Based Methods.Reliability Algorithms: FORM and SORM Methods.Variance-Based Methods.Managing the Tyranny of Parameters in Mathematical Modelling of Physical Systems.Bayesian Sensitivity Analysis.Graphical Methods.APPLICATIONS.Practical Experience in Applying Sensitivity and Uncertainty Analysis.Scenario and Parametric Sensitivity and Uncertainty Analysis in Nuclear Waste Disposal Risk Assessment: The Case of GESAMAC.Sensitivity Analysis for Signal Extraction in Economic Time Series.A Dataless Precalibration Analysis in Solid State Physics.Appplication 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.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).Comparing Different Sensitivity Analysis Methods on a Chemical Reactions Model.An Application of Sensitivity Analysis to Fish Population Dynamics.Global Sensitivity Analysis: A Quality Assurance Tool in Environmental Policy Modelling.CONCLUSIONS.Assuring the Quality of Models Designed for Predictive Tasks.Fortune and Future of Sensitivity Analysis.References.Appendix.Index....

Auteur

Andrea Saltelli, Joint Research Centre of the European Commission, Ispra, Unit of Applied Statistics and Econometrics. Presently leading the Econometric and Applied Statistics Unit of the Joint Research Centre, lead author Professor Saltelli has published many articles in numerous journals over the last 30 years. He is also the main author and main editor of two previous books (both for Wiley).

Texte du rabat

Mit Hilfe einer Sensitivitätsanalyse kann man feststellen, wie ein gegebenes Modell von den Eingabeparametern abhängt und unter welchen Umständen es instabil werden könnte. Die gute Modellierungspraxis kommt ohne solche Betrachtungen zukünftig nicht mehr aus! Ausgehend von einer Erläuterung der Grundprinzipien hilft Ihnen dieses Buch, eine Lösung für Ihre Modellierungsprobleme zu finden. Die Auswirkungen von Unsicherheiten oder Annahmen werden dabei besser durchschaubar.

Contenu

What is Sensitivity Analysis. Hitchhiker's Guide to Sensitivity Analysis. METHODS. Designs of Experiments. Screening Methods. Local Methods. Sampling-Based Methods. Reliability Algorithms: FORM and SORM Methods. Variance-Based Methods. Managing the Tyranny of Parameters in Mathematical Modelling of Physical Systems. Bayesian Sensitivity Analysis. Graphical Methods. APPLICATIONS. Practical Experience in Applying Sensitivity and Uncertainty Analysis. Scenario and Parametric Sensitivity and Uncertainty Analysis in Nuclear Waste Disposal Risk Assessment: The Case of GESAMAC. Sensitivity Analysis for Signal Extraction in Economic Time Series. A Dataless Precalibration Analysis in Solid State Physics. Appplication 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. 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). Comparing Different Sensitivity Analysis Methods on a Chemical Reactions Model. An Application of Sensitivity Analysis to Fish Population Dynamics. Global Sensitivity Analysis: A Quality Assurance Tool in Environmental Policy Modelling. CONCLUSIONS. Assuring the Quality of Models Designed for Predictive Tasks. Fortune and Future of Sensitivity Analysis. References. Appendix. Index.