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Theory of Decision under Uncertainty, Gilboa


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Автор: Gilboa
Название:  Theory of Decision under Uncertainty
ISBN: 9780521517324
Издательство: Cambridge Academ
Классификация:
ISBN-10: 052151732X
Обложка/Формат: Hardback
Страницы: 230
Вес: 0.43 кг.
Дата издания: 28/05/2009
Серия: Econometric society monographs
Язык: English
Иллюстрации: Black & white illustrations
Размер: 229 x 152 x 18
Читательская аудитория: economics, statistics, applied mathematics, operations research, engineering theory
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This book describes classical axiomatic theories of decision under uncertainty, critiques thereof, and alternative theories. It discusses the meaning of probability, focusing on the behavioral definition of subjective probability by Savage`s theorem. It presents non-additive and multiple prior theories, as well as the case-based approach to the formation of beliefs.


A First Course in Optimization Theory

Автор: Sundaram, Rangarajan K.
Название: A First Course in Optimization Theory
ISBN: 0521497701 ISBN-13(EAN): 9780521497701
Издательство: Cambridge Academ
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Цена: 6811.00 р.
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Описание: This book, first published in 1996, introduces students to optimization theory and its use in economics and allied disciplines.

Theory of Probability and Random Processes

Автор: Koralov
Название: Theory of Probability and Random Processes
ISBN: 3540254846 ISBN-13(EAN): 9783540254843
Издательство: Springer
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Цена: 8384.00 р.
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Описание: A one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of the content of this bookIt is structured in two parts: the first part providing a detailed discussion of Lebesgue integration, Markov chains, random walks, laws of large numbers, limit theorems, and their relation to Renormalization Group theory. The second part includes the theory of stationary random processes, martingales, generalized random processes, Brownian motion, stochastic integrals, and stochastic differential equations. One section is devoted to the theory of Gibbs random fields.This material is essential to many undergraduate and graduate courses. The book can also serve as a reference for scientists using modern probability theory in their research.

Investment under Uncertainty, Coalition Spillovers and Market Evolution in a Game Theoretic Perspective

Автор: Thijssen J.H.H
Название: Investment under Uncertainty, Coalition Spillovers and Market Evolution in a Game Theoretic Perspective
ISBN: 1402078773 ISBN-13(EAN): 9781402078774
Издательство: Springer
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Цена: 25155.00 р.
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Описание: New models and techniques are developed in this text to analyse economic dynamics in an uncertain environment.

Monetary Policy Under Uncertainty

Автор: Sauter Oliver
Название: Monetary Policy Under Uncertainty
ISBN: 3658049731 ISBN-13(EAN): 9783658049737
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Oliver Sauter analyzes three aspects of monetary policy under uncertainty. The second aspect is the proper examination and incorporation of uncertainty into a monetary policy framework. Thirdly, he focuses on the quantification of uncertainty from two different perspectives, either from a market perspective or from a central bank perspective.

Irreversible Decisions under Uncertainty

Автор: Svetlana Boyarchenko; Sergei Levendorskii
Название: Irreversible Decisions under Uncertainty
ISBN: 3642092934 ISBN-13(EAN): 9783642092930
Издательство: Springer
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Цена: 25853.00 р.
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Описание: Here, two highly experienced authors present an alternative approach to optimal stopping problems. The basic ideas and techniques of the approach can be explained much simpler than the standard methods in the literature on optimal stopping problems.

Shape Optimization under Uncertainty from a Stochastic Programming Point of View

Автор: Harald Held
Название: Shape Optimization under Uncertainty from a Stochastic Programming Point of View
ISBN: 3834809098 ISBN-13(EAN): 9783834809094
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Optimization problems whose constraints involve partial differential equations (PDEs) are relevant in many areas of technical, industrial, and economic app- cations. At the same time, they pose challenging mathematical research problems in numerical analysis and optimization. The present text is among the ?rst in the research literature addressing stochastic uncertainty in the context of PDE constrained optimization. The focus is on shape optimization for elastic bodies under stochastic loading. Analogies to ?nite dim- sional two-stage stochastic programming drive the treatment, with shapes taking the role of nonanticipative decisions.The main results concern level set-based s- chastic shape optimization with gradient methods involving shape and topological derivatives. The special structure of the elasticity PDE enables the numerical - lution of stochastic shape optimization problems with an arbitrary number of s- narios without increasing the computational effort signi?cantly. Both risk neutral and risk averse models are investigated. This monograph is based on a doctoral dissertation prepared during 2004-2008 at the Chair of Discrete Mathematics and Optimization in the Department of Ma- ematics of the University of Duisburg-Essen. The work was supported by the Deutsche Forschungsgemeinschaft (DFG) within the Priority Program "Optimi- tion with Partial Differential Equations." Rudiger Schultz Acknowledgments I owe a great deal to my supervisors, colleagues, and friends who have always supported, encouraged, andenlightenedmethroughtheirownresearch, comments, and questions.

Advances in Decision Making Under Risk and Uncertainty

Автор: Mohammed Abdellaoui; John D. Hey
Название: Advances in Decision Making Under Risk and Uncertainty
ISBN: 3642088007 ISBN-13(EAN): 9783642088001
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Uncertainty and Information Modeling.- Revealed Ambiguity and Its Consequences: Updating.- Dynamic Decision Making When Risk Perception Depends on Past Experience.- Representation of Conditional Preferences Under Uncertainty.- Subjective Information in Decision Making and Communication.- Risk Modeling.- Sensitivity Analysis in Decision Making: A Consistent Approach.- Alternation Bias and the Parameterization of Cumulative Prospect Theory.- Proposing a Normative Basis for the S-Shaped Value Function.- Experimental Individual Decision Making.- Individual Choice from a Convex Lottery Set: Experimental Evidence.- Temptations and Dynamic Consistency.- Monty Hall's Three Doors for Dummies.- Overconfidence in Predictions as an Effect of Desirability Bias.- Experimental Interactive Decision Making.- Granny Versus Game Theorist: Ambiguity in Experimental Games.- Guessing Games and People Behaviours: What Can We Learn?.- The Determinants of Individual Behaviour in Network Formation: Some Experimental Evidence.


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