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Stochastic Simulation: Algorithms and Analysis, S?ren Asmussen; Peter W. Glynn


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Автор: S?ren Asmussen; Peter W. Glynn
Название:  Stochastic Simulation: Algorithms and Analysis
ISBN: 9781441921468
Издательство: Springer
Классификация:





ISBN-10: 144192146X
Обложка/Формат: Paperback
Страницы: 476
Вес: 0.68 кг.
Дата издания: 19.11.2010
Серия: Stochastic Modelling and Applied Probability
Язык: English
Размер: 157 x 233 x 31
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book provides a broad treatment of sampling-based computational methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. General methods and model-specific algorithms are discussed.


Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 11246.00 р.
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Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.

Stochastic processes

Автор: Parzen, Emanuel
Название: Stochastic processes
ISBN: 0898714419 ISBN-13(EAN): 9780898714418
Издательство: Mare Nostrum (Eurospan)
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Цена: 9656.00 р.
Наличие на складе: Нет в наличии.

Описание: This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.

Stochastic Simulation Optimization for Discrete Event Systems: Perturbation Analysis, Ordinal Optimization and Beyond

Автор: Chen Chun-Hung, Jia Qing-Shan, Lee Loo Hay
Название: Stochastic Simulation Optimization for Discrete Event Systems: Perturbation Analysis, Ordinal Optimization and Beyond
ISBN: 9814513008 ISBN-13(EAN): 9789814513005
Издательство: World Scientific Publishing
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Цена: 12830.00 р.
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Описание: Discrete event systems (DES) have become pervasive in our daily lives. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling these stochastic simulations has long been a "hard nut to crack." The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y C Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions.

Stochastic Models, Statistical Methods, and Algorithms in Image Analysis

Автор: Piero Barone; Arnoldo Frigessi; Mauro Piccioni
Название: Stochastic Models, Statistical Methods, and Algorithms in Image Analysis
ISBN: 0387978100 ISBN-13(EAN): 9780387978109
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This volume comprises a collection of papers by world- renowned experts on image analysis. The papers range from survey articles to research papers, and from theoretical topics such as simulated annealing through to applied image reconstruction.

Two-Scale Stochastic Systems / Asymptotic Analysis and Control

Автор: Kabanov Yuri, Pergamenshchikov Sergei
Название: Two-Scale Stochastic Systems / Asymptotic Analysis and Control
ISBN: 3540653325 ISBN-13(EAN): 9783540653325
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Two-scale systems described by singularly perturbed SDEs have been the subject of ample literature. However, this new monograph develops subjects that were rarely addressed and could be given the collective description "Stochastic Tikhonov-Levinson theory and its applications." The book provides a mathematical apparatus designed to analyze the dynamic behaviour of a randomly perturbed system with fast and slow variables. In contrast to the deterministic Tikhonov-Levinson theory, the basic model is described in a more realistic way by stochastic differential equations. This leads to a number of new theoretical questions but simultaneously allows us to treat in a unified way a surprisingly wide spectrum of applications like fast modulations, approximate filtering, and stochastic approximation.

An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 27712.00 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Stochastic and Statistical Methods in Hydrology and Environmental Engineering: Time Series Analysis in Hydrology

Автор: Keith W. Hipel
Название: Stochastic and Statistical Methods in Hydrology and Environmental Engineering: Time Series Analysis in Hydrology
ISBN: 9048143799 ISBN-13(EAN): 9789048143795
Издательство: Springer
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Цена: 28732.00 р.
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Описание: Vol.4: Effective Environmental Management for Sustainable Development

Stochastic Simulation: Algorithms and Analysis

Автор: Asmussen
Название: Stochastic Simulation: Algorithms and Analysis
ISBN: 038730679X ISBN-13(EAN): 9780387306797
Издательство: Springer
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Цена: 6981.00 р.
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Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first  half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of  examples, exercises and applications students, practitioners and researchers in  probability, statistics, operations research, economics, finance, engineering  as well as biology and chemistry and physics will find the book of value.  Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of  Engineering at Stanford University. 


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