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Sensitivity analysis in practice : a guide to assessing scientific models

Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This℗¡ book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners.

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  • "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. This book offers an accessible introduction to sensitivity analysis. It covers all the latest research and illustrates concepts with numerous examples, applications, and case studies. The book 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."
  • "Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This℗¡ book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners."@en
  • "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.Sensitivity Analysis in Practice guides applied scientists through their modelling problem enabling them to choose and apply the most appropriate sensitivity analysis method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It includes discussion of implementation of the methods using SIMLAB freely available sensitivity analysis software.*Provides an accessible overview of the most widely used sensitivity analysis methods.*Covers a range of methodologies, including variance-based methods, Bayesian uncertainty estimation, selected screening methods and Monte Carlo filtering.*Opens with a detailed worked example to explain the motivation behind methods described.*Includes a range of further worked examples to illustrate the practical applications.*Discusses implementation of the methods using SIMLAB freely available sensitivity analysis software.*Contains a large number of references to sources for further reading.*Supported by a Website featuring a SIMLAB download, data sets and additional material.Sensitivity Analysis in Practice is primarily aimed at researchers and practitioners working in scientific modelling from statistics, mathematics, medicine, and environmental science. The book is suitable for applied scientists working with statistical models in virtually any discipline, including economics, biology, chemistry and engineering, as well as graduate students of statistical modelling"

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  • "Electronic books"@en
  • "Aufsatzsammlung"

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  • "Sensitivity analysis"
  • "Sensitivity analysis in practice : a guide to assessing scientific models"@en
  • "Sensitivity analysis in practice : a guide to assessing scientific models"
  • "Sensitivity Analysis"
  • "Sensitivity analysis in practice a guide to assessing scientific models"
  • "Sensitivity analysis in practice a guide to assessing scientific models"@en
  • "Sensitivity analysis of scientific models"
  • "Sensitivity analysis in practice : a guide to assessing acientific models"

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