TY - BOOK AU - Cursi, Eduardo Souza de TI - Uncertainty quantification with R: bayesian methods T2 - International Series in Operations Research & Management Science vol. 352 SN - 9783031482076 U1 - 001.434 PY - 2024/// CY - Cham PB - Springer KW - R--Computer program language KW - Data visualization N1 - Table of content: Basic Bayesian Probabilities Eduardo Souza de Cursi Pages 1-131 Beliefs Eduardo Souza de Cursi Pages 133-201 Information and Entropy Eduardo Souza de Cursi Pages 203-264 Maximum Entropy Eduardo Souza de Cursi Pages 265-320 Bayesian Inference Eduardo Souza de Cursi Pages 321-412 Sequential Bayesian Estimation Eduardo Souza de Cursi Pages 413-480 Back Matter Pages 481-486 [https://link.springer.com/book/10.1007/978-3-031-48208-3] N2 - 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. (https://link.springer.com/book/10.1007/978-3-031-48208-3) ER -