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Monte Carlo and Quasi-Monte Carlo Methods 2000, Kai-Tai Fang; Fred J. Hickernell; Harald Niederrei


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Автор: Kai-Tai Fang; Fred J. Hickernell; Harald Niederrei
Название:  Monte Carlo and Quasi-Monte Carlo Methods 2000
ISBN: 9783540427186
Издательство: Springer
Классификация:

ISBN-10: 354042718X
Обложка/Формат: Paperback
Страницы: 548
Вес: 0.80 кг.
Дата издания: 22.01.2002
Язык: English
Размер: 234 x 156 x 30
Основная тема: Mathematics
Подзаголовок: Proceedings of a Conference held at Hong Kong Baptist University, Hong Kong SAR, China, November 27 – December 1, 2000
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Contains the proceedings of the Fourth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing held in Hong Kong in 2000. It includes surveys of multidimensional numerical integration, low-discrepancy point sets, random number generation and applications.


Monte Carlo Methods in Financial Engineering

Автор: Glasserman
Название: Monte Carlo Methods in Financial Engineering
ISBN: 0387004513 ISBN-13(EAN): 9780387004518
Издательство: Springer
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Цена: 11179.00 р.
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Описание: From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not."

Monte Carlo Methods in Bayesian Computation

Автор: Chen Ming-Hui, Shao Qi-Man, Ibrahim Joseph G.
Название: Monte Carlo Methods in Bayesian Computation
ISBN: 0387989358 ISBN-13(EAN): 9780387989358
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book examines advanced Bayesian computational methods. It presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo methods for estimation of posterior quantities, improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. The authors also discuss computions involving model comparisons, including both nested and non-nested models, marginal likelihood methods, ratios of normalizing constants, Bayes factors, the Savage-Dickey density ratio, Stochastic Search Variable Selection, Bayesian Model Averaging, the reverse jump algorithm, and model adequacy using predictive and latent residual approaches.The book presents an equal mixture of theory and applications involving real data. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners.Ming-Hui Chen is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute, Qu-Man Shao is Assistant Professor of Mathematics at the University of Oregon. Joseph G. Ibrahim is Associate Professor of Biostatistics at the Harvard School of Public Health and Dana-Farber Cancer Institute.

Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

Автор: Harald Niederreiter; Peter J. Shiue
Название: Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
ISBN: 0387945776 ISBN-13(EAN): 9780387945774
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Scientists and engineers are increasingly making use of simulation methods to solve problems which are insoluble by analytical techniques. Monte Carlo methods which make use of probabilistic simulations are frequently used in areas such as numerical integration, complex scheduling, queueing networks, and large-dimensional simulations.

Monte Carlo and Quasi-Monte Carlo Methods 1996

Автор: Harald Niederreiter; Peter Hellekalek; Gerhard Lar
Название: Monte Carlo and Quasi-Monte Carlo Methods 1996
ISBN: 038798335X ISBN-13(EAN): 9780387983356
Издательство: Springer
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Цена: 13275.00 р.
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Описание: Monte Carlo methods are numerical methods based on random sampling and quasi-Monte Carlo methods are their deterministic versions. These proceedings will be of interest to graduate students and researchers in Monte Carlo and quasi-Monte Carlo methods, to numerical analysts, and to practitioners of simulation methods.

Monte Carlo and Quasi-Monte Carlo Methods 2012

Автор: Josef Dick; Frances Y. Kuo; Gareth W. Peters; Ian
Название: Monte Carlo and Quasi-Monte Carlo Methods 2012
ISBN: 3642410944 ISBN-13(EAN): 9783642410949
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February 2012.

Monte-Carlo and Quasi-Monte Carlo Methods 1998

Автор: Harald Niederreiter; Jerome Spanier
Название: Monte-Carlo and Quasi-Monte Carlo Methods 1998
ISBN: 354066176X ISBN-13(EAN): 9783540661764
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book represents the refereed proceedings of the Third International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at Claremont Graduate University in 1998.

Monte Carlo and Quasi-Monte Carlo Sampling

Автор: Christiane Lemieux
Название: Monte Carlo and Quasi-Monte Carlo Sampling
ISBN: 1441926763 ISBN-13(EAN): 9781441926760
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Quasi-Monte Carlo methods have become an increasingly popular alternative to Monte Carlo methods over the last two decades. This book presents all of the essential tools for using quasi-Monte Carlo sampling on practical problems, especially in finance.

Strategies for Quasi-Monte Carlo

Автор: Bennett L. Fox
Название: Strategies for Quasi-Monte Carlo
ISBN: 1461373794 ISBN-13(EAN): 9781461373797
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Strategies for Quasi-Monte Carlo builds a framework to design and analyze strategies for randomized quasi-Monte Carlo (RQMC).

Strategies for Quasi-Monte Carlo

Автор: Bennett L. Fox
Название: Strategies for Quasi-Monte Carlo
ISBN: 0792385802 ISBN-13(EAN): 9780792385806
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Offers a framework to design and analyze strategies for randomized quasi-Monte Carlo (RQMC). This book provides illustrations for problems involving Poisson processes or Gaussian processes. It is useful for those individuals interested in improving simulation efficiency with more than incremental increases.

Introduction to Robust and Quasi-Robust Statistical Methods

Автор: W.J.J. Rey
Название: Introduction to Robust and Quasi-Robust Statistical Methods
ISBN: 3540128662 ISBN-13(EAN): 9783540128663
Издательство: Springer
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Цена: 13275.00 р.
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Multivariable Feedback: A Quasi-Classical Approach

Автор: Y. S. Hung; A. G. J. MacFarlane
Название: Multivariable Feedback: A Quasi-Classical Approach
ISBN: 3540119027 ISBN-13(EAN): 9783540119029
Издательство: Springer
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Цена: 12157.00 р.
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Monte Carlo and Quasi-Monte Carlo Methods 2012

Автор: Josef Dick; Frances Y. Kuo; Gareth W. Peters; Ian
Название: Monte Carlo and Quasi-Monte Carlo Methods 2012
ISBN: 3662514389 ISBN-13(EAN): 9783662514382
Издательство: Springer
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Цена: 19564.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February 2012.


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