**ISBN:** 0470743824

**Author:** Andrea Saltelli,K. Chan,E. M. Scott

**Language:** English

**Publisher:** Wiley; 1 edition (March 16, 2009)

**Pages:** 494

**Category:** Mathematics

**Subcategory:** Science

**Rating:** 4.5

**Votes:** 373

**Size Fb2:** 1682 kb

**Size ePub:** 1205 kb

**Size Djvu:** 1617 kb

**Other formats:** txt docx lrf lit

Sensitivity Analysis. Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters.

Sensitivity Analysis. E. M. Scott University of Glasgow, UK. 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.

Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters.

Global Sensitivity Analysis: An Introduction. Eds. 2000, a multi-author book. Saltelli, . K. Chan and M. Scott, Ed. 2000, Handbook of Sensitivity Analysis, John Wiley & Sons publishers, Probability and Statistics series. Abstract: This presentation aims to introduce global sensitivity analysis (SA), targeting an audience unfamiliar with the topic, and to give practical hints about the associated advantages and the effort needed. Prescriptions have been issued for sensitivity analysis of models when these used for policy analysis. 1999, Sensitivity analysis.

Saltelli, . In Sensitivity Analysis; Chan, . Scott, . Ed. John Wiley & Sons, Chichester, 2000. J. Haug, K. Choi and V. Komkov, Design Sensitivity Analysis of Structural Systems, Academic Press, New York, NY, 1986. 29. Turányi, . Rabitz, H. John Wiley & Sons, Chichester, 2000; p 81. 30. Varma, . Morbidelli . Wu H. In Parametric Sensitivity in Chemical Systems; Cambridge, 1999. 48. Kleiber, H. Antunez, T. D. Hien and P. Kowalczyk, Parameter Sensitivity in Nonlinear Mechanics: Theory and Finite Element Computations, John Wiley & Sons, New York, NY, 1997. Andrea Saltelli, K. Chan, E. Scott . The book introduces the modeller to the entire casual assessment chain, from data to predictions, whilst explaining the impact of source uncertainties and framing assumptions.

Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem.

Sensitivity Analysis book.

Saltelli . Vidoni . Mascherini M. (2009) Recommended practices in global sensitivity analysis.

forthcoming)Google Scholar. Tarantola, . Campolongo, . and Ratto, . 2004, Sensitivity Analysis in Practice. A Guide to Assessing Scientific Models, John Wiley and Sons, Chichester, New York. Saltelli . Laba . Mysiak J. (eds) Uncertainties in Environmental Modelling and Consequences for Policy Making. NATO Science for Peace and Security Series C: Environmental Security.

Books by A Saltelli with Solutions. Chan, Andrea Saltelli, K. Chan, Scott Bernard, E. Scott, A. Saltelli, E. Marian Scott. Stefano Tarantola, Francesca Campolongo, Marco Ratto, A. Saltelli, Andrea Saltelli. Join Chegg Study and get: Guided textbook solutions created by Chegg experts.

Sensitivity analysis is used to ascertain how a given modeloutput depends upon the input parameters. This is an importantmethod for checking the quality of a given model, as well as apowerful tool for checking the robustness and reliability of itsanalysis. The topic is acknowledged as essential for good modellingpractice and is an implicit part of any modelling field.

Offers an accessible introduction to sensitivity analysis.Covers all the latest research.Illustrates concepts with numerous examples, applications andcase studies.Includes contributions from the leading researchers active indeveloping strategies for sensitivity analysis.The principles of sensitivity analysis are carefully describedand suitable methods for approaching many types of problems aregiven. The book introduces the modeller to the entire casualassessment chain, from data to predictions, whilst explaining theimpact of source uncertainties and framing assumptions. A‘hitch-hikers guide’ is included to allow the moreexperienced reader to readily access specific applications.

Modellers from a wide range of disciplines, includingbiostatistics, economics, environmental impact assessment,chemistry and engineering will benefit greatly from the numerousexamples and applications.

"Presents many different sensitivity analysis methodologies anddemonstrates their usefulness in scientific research."(Zentralblatt MATH)

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