000			02383nam a22002177a 4500
005			20250112170936.0
008			250109b |||||||| |||| 00| 0 eng d
020			_a9783031482076
082			_a001.434 _bCUR
100			_aCursi, Eduardo Souza de _920286
245			_aUncertainty quantification with R: _bbayesian methods
260			_bSpringer _aCham _c2024
300			_aviii, 486 p.
365			_aEUR _b139.99
490			_aInternational Series in Operations Research & Management Science vol. 352
500			_aTable 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]
520			_aThis 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)
650			_aR--Computer program language
650			_aData visualization _912153
942			_cBK _2ddc
999			_c8380 _d8380