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[GLOBAL SENSITIVITY ANALYSIS] 

Global Sensitivity Analysis: The Primer

   
지은이 Andrea Saltelli   |   출판사 WILEY  |   발행일 2008년 03월 01일   |   언어 : English
 
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판매가 170,800원128,100원 25%
마일리지 1% 1,710원
발행일 2008-03-01 | 중량: 0.56 kg | 사이즈: 17.3*22.9*2.2 cm
ISBN 0470059974 | 9780470059975
기타정보 원서 | 292쪽 | $ 122 | Hardcover
예상입고일 15~20일 소요예정 (근무일기준)
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    Complex mathematical and computational models are used in all areasof society and technology and yet model based science isincreasingly contested or refuted, especially when models areapplied to controversial themes in domains such as health, theenvironment or the economy. More stringent standards of proofs aredemanded from model-based numbers, especially when these numbersrepresent potential financial losses, threats to human health orthe state of the environment. Quantitative sensitivity analysis isgenerally agreed to be one such standard.

    Mathematical models are good at mapping assumptions intoinferences. A modeller makes assumptions about laws pertaining tothe system, about its status and a plethora of other, often arcane,system variables and internal model settings. To what extent can werely on the model-based inference when most of these assumptionsare fraught with uncertainties? Global Sensitivity Analysis offersan accessible treatment of such problems via  quantitativesensitivity analysis, beginning with the first principles andguiding the reader through the full range of recommended practiceswith a rich set of solved exercises. The text explains themotivation for sensitivity analysis, reviews the requiredstatistical concepts, and provides a guide to potentialapplications.

    The book:

    • Provides a self-contained treatment of the subject, allowingreaders to learn and practice global sensitivity analysis withoutfurther materials.
    • Presents ways to frame the analysis, interpret its results, andavoid potential pitfalls.
    • Features numerous exercises and solved problems to helpillustrate the applications.
    • Is authored by leading sensitivity analysis practitioners,combining a range of disciplinary backgrounds.

    Postgraduate students and practitioners in a wide range ofsubjects, including statistics, mathematics, engineering, physics,chemistry, environmental sciences, biology, toxicology, actuarialsciences, and econometrics will find much of use here. This bookwill prove equally valuable to engineers working on risk analysisand to financial analysts concerned with pricing and hedging.



    Complex mathematical and computational models are used in all areasof society and technology and yet model based science isincreasingly contested or refuted, especially when models areapplied to controversial themes in domains such as health, theenvironment or the economy. More stringent standards of proofs aredemanded from model-based numbers, especially when these numbersrepresent potential financial losses, threats to human health orthe state of the environment. Quantitative sensitivity analysis isgenerally agreed to be one such standard.

    Mathematical models are good at mapping assumptions intoinferences. A modeller makes assumptions about laws pertaining tothe system, about its status and a plethora of other, often arcane,system variables and internal model settings. To what extent can werely on the model-based inference when most of these assumptionsare fraught with uncertainties? Global Sensitivity Analysis offersan accessible treatment of such problems via quantitativesensitivity analysis, beginning with the first principles andguiding the reader through the full range of recommended practiceswith a rich set of solved exercises. The text explains themotivation for sensitivity analysis, reviews the requiredstatistical concepts, and provides a guide to potentialapplications.
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