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Basics and Trends in Sensitivity Analysis: Theory and Practice in R (Computational Science and Engineering) - Softcover
Inhaltsangabe
This book provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. The authors use a practical point of view and real case studies as well as numerous examples, and applications of the different approaches are illustrated throughout using R code to explain their usage and usefulness in practice.
Basics and Trends in Sensitivity Analysis: Theory and Practice in R covers a lot of material, including theoretical aspects of Sobol’ indices as well as sampling-based formulas, spectral methods, and metamodel-based approaches for estimation purposes; screening techniques devoted to identifying influential and noninfluential inputs; variance-based measures when model inputs are statistically dependent (and several other approaches that go beyond variance-based sensitivity measures); and a case study in R related to a COVID-19 epidemic model where the full workflow of sensitivity analysis combining several techniques is presented.
This book is intended for engineers, researchers, and undergraduate students who use complex numerical models and have an interest in sensitivity analysis techniques and is appropriate for anyone with a solid mathematical background in basic statistical and probability theories who develops and uses numerical models in all scientific and engineering domains.
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Über die Autorin bzw. den Autor
Sébastien Da Veiga is a senior expert in Statistics and Optimization at Safran. His research interests include computer experiments modelling, sensitivity analysis, optimization problems, kernel methods, and random forests.
Fabrice Gamboa is currently a professor at Toulouse University. His research interests include asymptotic statistics, random matrices and large deviations, statistical modelling, and industrial applications.
Bertrand Iooss is a senior researcher at EDF R&D, leading a project on uncertainty quantification and machine learning techniques for nuclear engineering processes. His research interests include computer experiments modelling, sensitivity analysis, geostatistics, machine learning validation, and explainability.
Clémentine Prieur is a professor at University Grenoble Alpes. Her research interests include properties of dependent stochastic processes and modelling of spatio-temporal dependence.
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Basics and Trends in Sensitivity Analysis: Theory and Practice in R
Verlag:
SIAM - Society for Industrial and Applied Mathematics, 2021
ISBN 10: 1611976685
ISBN 13: 9781611976687
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Basics and Trends in Sensitivity Analysis (Paperback)
ISBN 10: 1611976685
ISBN 13: 9781611976687
Neu
Paperback
Anbieter: Grand Eagle Retail, Mason, OH, USA
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: new. Paperback. This book provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. The authors use a practical point of view and real case studies as well as numerous examples, and applications of the different approaches are illustrated throughout using R code to explain their usage and usefulness in practice. Basics and Trends in Sensitivity Analysis: Theory and Practice in R covers a lot of material, including theoretical aspects of Sobol indices as well as sampling-based formulas, spectral methods, and metamodel-based approaches for estimation purposes; screening techniques devoted to identifying influential and noninfluential inputs; variance-based measures when model inputs are statistically dependent (and several other approaches that go beyond variance-based sensitivity measures); and a case study in R related to a COVID-19 epidemic model where the full workflow of sensitivity analysis combining several techniques is presented.This book is intended for engineers, researchers, and undergraduate students who use complex numerical models and have an interest in sensitivity analysis techniques and is appropriate for anyone with a solid mathematical background in basic statistical and probability theories who develops and uses numerical models in all scientific and engineering domains. Provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. Throughout, readers can practice applications using the accompanying R code. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781611976687
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
Basics and Trends in Sensitivity Analysis (Paperback)
ISBN 10: 1611976685
ISBN 13: 9781611976687
Neu
Paperback
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: new. Paperback. This book provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. The authors use a practical point of view and real case studies as well as numerous examples, and applications of the different approaches are illustrated throughout using R code to explain their usage and usefulness in practice. Basics and Trends in Sensitivity Analysis: Theory and Practice in R covers a lot of material, including theoretical aspects of Sobol indices as well as sampling-based formulas, spectral methods, and metamodel-based approaches for estimation purposes; screening techniques devoted to identifying influential and noninfluential inputs; variance-based measures when model inputs are statistically dependent (and several other approaches that go beyond variance-based sensitivity measures); and a case study in R related to a COVID-19 epidemic model where the full workflow of sensitivity analysis combining several techniques is presented.This book is intended for engineers, researchers, and undergraduate students who use complex numerical models and have an interest in sensitivity analysis techniques and is appropriate for anyone with a solid mathematical background in basic statistical and probability theories who develops and uses numerical models in all scientific and engineering domains. Provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. Throughout, readers can practice applications using the accompanying R code. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9781611976687
Anzahl: 1 verfügbar