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008			230222s2023 sz | s |||| 0|eng d
020			_a9783031177859
024	7		_a10.1007/978-3-031-17785-9 _2doi
040			_aES-VaUEC _bspa _cES-VaUEC
050	0	4	_aT57.6-.97 _b2024
100	1		_aSouza de Cursi, Eduardo. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	0	0	_aUncertainty Quantification using R _cby Eduardo Souza de Cursi
250			_a1st ed 2023
264		1	_aCham _c2023 _bSpringer International Publishing
300	0	0	_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aInternational Series in Operations Research & Management Science, _x2214-7934 ; _v335
505	0		_a1. Introduction -- 2. Some tips to use R and RStudio -- 3. Probabilities and Random Variables -- 4. Representation of random variables -- 5. Stochastic processes -- 6. Uncertain Algebraic Equations -- 7. Random Differential Equations -- 8. UQ in Game Theory -- 9. Optimization under uncertainty -- 10. Reliability.
520			_aThis book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. 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 uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python 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 linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning. .
830		0	_aInternational Series in Operations Research & Management Science, _x2214-7934 ; _v335
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-17785-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
912			_aZDB-2-BUM
912			_aZDB-2-SXBM
942			_2lcc _cLE
988			_aSpringer_Business_2023
999			_c238663 _d238663