Sensitivity analysis /
作者: edited by Andrea Saltelli, Karen Chan, E. Marian Scott.
出版社:
简介:Summary:
Publisher Summary 1
Scientists who model systems in a wide range of disciplines explain their methods for sensitivity analysis, which ascertains how the variation, numerical or otherwise, in the output of a model, diagnostic or prognostic, can be apportioned, qualitatively or quantitatively, to different sources of variation, and how the given model depends on the information fed into it. They introduce the entire causal assessment chain, from data to predictions, and explain the impact of source uncertainties and the framing assumptions. The CiP data shows the title as Mathematical and Statistical Methods: Sensitivity Analysis. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Publisher Summary 2
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.
? Offers an accessible introduction to sensitivity analysis
? Covers all the latest research
? Illustrates concepts with numerous examples, applications and case studies
? Includes contributions form the leading researchers active in developing strategies for sensitivity analysis
The principles of sensitivity analysis area carefully described, and suitable methods for approaching many types of problems are given. The book introduces the modeller to the entire causal assessment chain, from data to predictions, whilst explaining the impact of source uncertainties and framing assumptions. A 'hitch-hiker's guide' is included to allow the more experienced reader to readily access specific applications.
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.