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Springer Uncertainty Quantification using R - Math Book

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Description

Master the techniques of uncertainty quantification with this rigorous and practical guide from Springer. Part of the International Series in Operations Research and Management Science, this volume provides the mathematical arguments necessary to establish clear assumptions while maintaining a strong focus on real-world applications. Designed for students and professionals, the content covers applied probability to ensure accessibility. By integrating R and Python, the book enables readers to solve complex problems involving a significant number of variables. This text is an essential resource for those studying optimization and mathematical modeling through computational tools.

Key Features

This Springer publication provides a rigorous and practical presentation of uncertainty quantification techniques.

Includes mathematical arguments and clearly established assumptions for a high level of academic rigor.

Features applications in both R and Python to help readers solve complex problems with many variables.

Covers practical aspects of applied probability to make the content accessible to students.

Belongs to the International Series in Operations Research and Management Science, volume 335.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
23 February 2023
Listed Since
25 August 2022

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