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Uncertainty Quantification with R

Bayesian Methods de

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Springer


Paru le : 2024-05-06

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Description

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.
Pages
486 pages
Collection
n.c
Parution
2024-05-06
Marque
Springer
EAN papier
9783031482076
EAN PDF
9783031482083
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
48
Taille du fichier
18063 Ko
Prix
147,69 €
EAN EPUB
9783031482083
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
48
Taille du fichier
108360 Ko
Prix
147,69 €

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