Uncertainty Quantification with R: Bayesian Methods: 352 (International Series in Operations Research & Management Science, 352) - Tapa dura
Sinopsis
This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. 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 Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R 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.
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Acerca del autor
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.
De la contraportada
This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. 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 Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R 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 basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning."Sobre este título" puede pertenecer a otra edición de este libro.
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Uncertainty Quantification with R: Bayesian Methods (International Series in Operations Research & Management Science, 352)
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Uncertainty Quantification with R
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions . Nº de ref. del artículo: 1155872321
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Uncertainty Quantification with R
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. 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 Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R 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 basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning. 496 pp. Englisch. Nº de ref. del artículo: 9783031482076
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Uncertainty Quantification with R : Bayesian Methods
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Condición: Sehr gut. Zustand: Sehr gut | Seiten: 496 | Sprache: Englisch | Produktart: Bücher | This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. 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 Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R 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 basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning. Nº de ref. del artículo: 42835047/2
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Uncertainty Quantification with R: Bayesian Methods (International Series in Operations Research & Management Science, 352)
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Uncertainty Quantification with R: Bayesian Methods (International Series in Operations Research & Management Science, 352)
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Uncertainty Quantification with R
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Springer, Springer Mai 2024, 2024
ISBN 10: 3031482077
ISBN 13: 9783031482076
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. 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 Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R 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 basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 496 pp. Englisch. Nº de ref. del artículo: 9783031482076
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Uncertainty Quantification with R : Bayesian Methods
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. 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 Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R 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 basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning. Nº de ref. del artículo: 9783031482076
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