TY - BOOK AU - Souza de Cursi,Eduardo ED - SpringerLink (Online service) TI - Uncertainty Quantification with R: Bayesian Methods T2 - International Series in Operations Research & Management Science, SN - 9783031482083 AV - T57.6-.97 PY - 2024/// CY - Cham PB - Springer Nature Switzerland, Imprint: Springer KW - Operations research KW - Production management KW - Probabilities KW - Mathematical optimization KW - Statistics  KW - Operations Research and Decision Theory KW - Operations Management KW - Applied Probability KW - Discrete Optimization KW - Bayesian Inference N1 - Introduction- 1 -- Basic Bayesian Probabilities-2 -- Beliefs-3 -- Information and Entropy-4 -- Maximum of Entropy-5 -- Bayesian Inference-6 -- Sequential Bayesian Estimation 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 UR - https://doi.org/10.1007/978-3-031-48208-3 ER -