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Modeling Uncertainty

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Modeling Uncertainty Synopsis

Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum, it is a book of considerable interest to a broad range of academic researchers and students of stochastic systems.

About This Edition

ISBN: 9780792374633
Publication date: 5th November 2019
Author: Sidney Yakowitz, Moshe Dror, Pierre LÉcuyer, Ferenc Szidarovszky
Publisher: Springer an imprint of Springer US
Format: Hardback
Pagination: 770 pages
Series: International Series in Operations Research & Management Science
Genres: Probability and statistics
Stochastics
Management decision making
Operational research