Uncertainty Quantification with R
Bayesian Methods
Series: International Series in Operations Research & Management Science; 352;
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Product details:
- Edition number 2024
- Publisher Springer Nature Switzerland
- Date of Publication 7 May 2024
- Number of Volumes 1 pieces, Book
- ISBN 9783031482076
- Binding Hardback
- No. of pages486 pages
- Size 235x155 mm
- Language English
- Illustrations VIII, 486 p. 111 illus. Illustrations, black & white 560
Categories
Long 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.
Table of Contents:
Introduction- 1.- Basic Bayesian Probabilities-2.- Beliefs-3.- Information and Entropy-4.- Maximum of Entropy-5.- Bayesian Inference-6.- Sequential Bayesian Estimation.
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