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Uncertainty Quantification and Stochastic Modelling with EXCEL
Title
Uncertainty Quantification and Stochastic Modelling with EXCEL [electronic resource] / by Eduardo Souza de Cursi.
ISBN
9783030777579
Edition
1st ed. 2022.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2022.
Physical Description
1 online resource (XI, 531 p.) 765 illus., 600 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool. Also included are solutions to uncertainty problems involving stochastic methods. The list of topics specially covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi objective optimization, and Game Theory, as well as linear algebraic equations, and probability and statistics. The book also provides a selection of numerical methods developed for Excel, in order to enhance readers' understanding. As such, it offers a valuable guide for all graduate and undergraduate students in the fields of economics, business administration, civil engineering, and others that rely on Excel as a research tool.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
February 10, 2022
Series
Springer Texts in Business and Economics,
Contents
Chapter 1: Some tips to use EXCEL
Chapter 2: Some useful Numerical Methods
Chapter 3: Probabilities with EXCEL
Chapter 4: Stochastic Processes
Chapter 5: Representation of Random Variables
Chapter 6: Uncertain Algebraic Equations
Chapter 7: Random Differential Equations
Chapter 8: UQ in Game Theory
Chapter 9: Optimization under uncertainty
Chapter 10: Reliability
Bibliography
Index.
Subjects
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