Uncertainty Quantification Using R: 335 - Rilegato

Cursi, Eduardo Souza De

Rilegato

ISBN 10: 3031177843 ISBN 13: 9783031177842

Casa editrice: Springer Nature, 2023

Riassunto

This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems.   

The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.  

Su questo libro

Informazioni sull?autore

Eduardo Souza De Cursi is a professor at the National Institute for Applied Sciences (INSA) in Rouen, France, where he serves as Dean of International Affairs and Director of the Laboratory of Mechanics of Normandy. He is also the Editor-in-Chief of "Computational and Applied Mathematics", a journal of the Brazilian Society of Computational and Applied Mathematics that is published with Springer. Prof. De Cursi holds a PhD in Sciences/Mathematics from the Université Des Sciences et Techniques Du Languedoc, USTL, France, and has over 35 years’ experience in research, teaching and technology transfer.

Dalla quarta di copertina

This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems.   

The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.  

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 3031177843
• ISBN 13: 9783031177842
• Rilegatura: Copertina rigida
• Numero di pagine: 776
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania