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Springer Modeling Uncertainty - Stochastic Theory and Methods

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Description

Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications serves as a significant academic volume dedicated to the work of Sid Yakowitz. This collection brings together the insights of fifty internationally recognized scholars who have contributed thirty specialized papers to the field. Each contribution underwent a rigorous review process to ensure high academic standards and quality for researchers and practitioners. The text covers a wide range of essential topics including probability, statistics, and economics. Readers can explore advanced concepts in stochastic optimization, control theory, regression analysis, and simulation. This volume is part of the International Series in Operations Research and Management Science, making it a valuable resource for those studying complex decision-making processes and mathematical modeling in uncertain environments.

Key Features

Comprehensive collection of thirty papers contributed by fifty internationally known scholars in the field.

Rigorous academic quality ensured through a careful review and revision process for the majority of submissions.

Wide range of subject coverage including probability, statistics, economics, and stochastic optimization.

In-depth exploration of control theory, regression analysis, and simulation techniques.

Part of the respected International Series in Operations Research and Management Science, volume 46.

Dedicated volume honoring the professional contributions and legacy of Sid Yakowitz.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
27 September 2019
Listed Since
20 December 2018

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