书目名称 | Uncertainty Quantification using R | 编辑 | Eduardo Souza de Cursi | 视频video | | 概述 | Presents the theory and methodology of uncertainty quantification, with applications in R and Python.Uses R and Python to solve complex, multivariate problems.Emphasizes practical applications of unce | 丛书名称 | International Series in Operations Research & Management Science | 图书封面 |  | 描述 | .This 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 | 出版日期 | Book 2023 | 关键词 | numerical methods; Model selection and estimation; Linear Algebraic Equations; Game Theory; Reliability | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-17785-9 | isbn_softcover | 978-3-031-17787-3 | isbn_ebook | 978-3-031-17785-9Series ISSN 0884-8289 Series E-ISSN 2214-7934 | issn_series | 0884-8289 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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