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Sensitivity Auditing
Posted by Jeroen on Friday, November 25 2011 @ 12:11:02 CET
News and announcements Sensitivity Auditing, recommended reading:
  • Andrea Saltelli (2011) Sensitivity auditing. Gauging model quality in relation to model use.
  • Andrea Saltelli (2002) Global Sensitivity Analysis: An Introduction. EU ISPRA
  • Andrea Saltelli and Beatrice D’Hombres (2010) Sensitivity analysis didn’t help. A practitioner’s critique of the Stern review. Global Environmental Change 20 (2010) 298–302.
  • Andrea Saltelli and Paola Annoni (2010). How to avoid a perfunctory sensitivity analysis, Environmental Modelling & Software 25, 1508-1517.
  • Andrea Saltelli and Silvio Funtowicz (2004) The Precautionary Principle: implications for risk management strategies International Journal of Occupational Medicine and Environmental Health, 2004; 17(1): 47-58.

  • Recommended books

    Saltelli et al, 2008, Global sensitivity analysis: the primer
    Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.

    Saltelli et al., 2004, Sensitivity Analysis in Practice: a guide to assessing scientific models
    Sensitivity analysis is the study of how variation in the output of a statistical model can be apportioned, qualitatively or quantitatively, to different sources of variation. It should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. Choosing the most appropriate method of sensitivity analysis for a particular model can be complex, and depends on a number of factors.

    Saltelli et al., 2000, 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. The topic is acknowledged as essential for good modelling practice, and is an implicit part of any modelling field.

    See also http://sensitivity-analysis.jrc.ec.europa.eu/



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