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Monte Carlo Methods in Bayesian Computation, Chen Ming-Hui, Shao Qi-Man, Ibrahim Joseph G.


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Цена: 15427р.
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Склад Англия: 652 шт.  Склад Америка: 134 шт.  
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Автор: Chen Ming-Hui, Shao Qi-Man, Ibrahim Joseph G.
Название:  Monte Carlo Methods in Bayesian Computation   (Чен Минг-Уй: Методы Монте-Карло в байесовских расчетах)
Издательство: Springer
Классификация:
Вероятность и статистика
Математическое и статистическое программное обеспечение

ISBN: 0387989358
ISBN-13(EAN): 9780387989358
ISBN: 0-387-98935-8
ISBN-13(EAN): 978-0-387-98935-8
Обложка/Формат: Hardback
Страницы: 386
Вес: 0.72 кг.
Дата издания: 2001
Серия: Springer Series in Statistics
Язык: ENG
Издание: 1st ed. 2000. corr.
Иллюстрации: 1, black & white illustrations
Размер: 24.23 x 16.31 x 2.46 cm
Читательская аудитория: Postgraduate, research & scholarly
Ссылка на Издательство: Link
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Поставляется из: Германии
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.
Дополнительное описание: Илюстрации: 20
Круг читателей: Researchers,graduate students
Язык: eng
Издание: 1st ed. 2000. Corr. 2nd p
Оглавление: Introduction * Markov Chain Monte Carlo Sampling * Basic Monte Carlo Methods for Estimating Posterior Quantities * Estimating Marginal Posterior Densities * Estimating Ratios of Normalizing Constants * Monte Carlo Methods for Constrained Parameter Problems * Computing Bayesian Credible and HPD Intervals * Bayesian Approaches for Comparing Non-Nested Models * Bayesian Variable Section * Other Topics





Bayesian Analysis with Stata

Автор: Thompson John
Название: Bayesian Analysis with Stata
ISBN: 1597181412 ISBN-13(EAN): 9781597181419
Издательство: Taylor&Francis
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Цена: 5851 р.
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Описание:

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata's data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability.

The book emphasizes practical data analysis from the Bayesian perspective, and hence covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of the results. Every topic is illustrated in detail using real-life examples, mostly drawn from medical research.

The book takes great care in introducing concepts and coding tools incrementally so that there are no steep patches or discontinuities in the learning curve. The book's content helps the user see exactly what computations are done for simple standard models and shows the user how those computations are implemented. Understanding these concepts is important for users because Bayesian analysis lends itself to custom or very complex models, and users must be able to code these themselves.

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: 6544 р.
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Описание: Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques.This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios.The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential.The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry.Mathematical Reviews, 2004: "... this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context."

Bayesian computation with R

Автор: Albert, Jim
Название: Bayesian computation with R
ISBN: 0387922970 ISBN-13(EAN): 9780387922973
Издательство: Springer
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Цена: 5609 р.
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Описание: There has been a dramatic growth in the development and application of Bayesian inferential methods. This book introduces Bayesian modeling by the use of computation using the R language. The new edition contains changes in the R code illustrations.

Statistical DNA Forensics - Theory, Methods and Computation

Автор: Fung
Название: Statistical DNA Forensics - Theory, Methods and Computation
ISBN: 0470066369 ISBN-13(EAN): 9780470066362
Издательство: Wiley
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Цена: 8668 р.
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Описание: Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed, and presented correctly. With the recent advances in computer technology, this methodology is more complex than ever before. There are a growing number of books in the area but none are devoted to the computational analysis of evidence.

Image Analysis, Random Fields and Markov Chain Monte Carlo Methods / A Mathematical Introduction

Автор: Winkler Gerhard
Название: Image Analysis, Random Fields and Markov Chain Monte Carlo Methods / A Mathematical Introduction
ISBN: 3540442138 ISBN-13(EAN): 9783540442134
Издательство: Springer
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Цена: 10284 р.
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Описание: This second edition of G. Winkler's successful book on random field approaches to image analysis, related Markov Chain Monte Carlo methods, and statistical inference with emphasis on Bayesian image analysis concentrates more on general principles and models and less on details of concrete applications. Addressed to students and scientists from mathematics, statistics, physics, engineering, and computer science, it will serve as an introduction to the mathematical aspects rather than a survey. Basically no prior knowledge of mathematics or statistics is required.The second edition is in many parts completely rewritten and improved, and most figures are new. The topics of exact sampling and global optimization of likelihood functions have been added. This second edition comes with a CD-ROM by F. Friedrich,containing a host of (live) illustrations for each chapter. In an interactive environment, readers can perform their own experiments to consolidate the subject.

Monte Carlo Statistical Methods

Автор: Robert
Название: Monte Carlo Statistical Methods
ISBN: 0387212396 ISBN-13(EAN): 9780387212395
Издательство: Springer
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Цена: 9349 р.
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Описание: We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

Monte Carlo Methods in Finance

Автор: Peter Jckel
Название: Monte Carlo Methods in Finance
ISBN: 047149741X ISBN-13(EAN): 9780471497417
Издательство: Wiley
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Цена: 9928 р.
Наличие на складе: Поставка под заказ.

Описание: An invaluable resource for quantitative analysts who need to run models that assist in option pricing and risk management. This concise, practical hands on guide to Monte Carlo simulation introduces standard and advanced methods to the increasing complexity of derivatives portfolios. Ranging from pricing more complex derivatives, such as American and Asian options, to measuring Value at Risk, or modelling complex market dynamics, simulation is the only method general enough to capture the complexity and Monte Carlo simulation is the best pricing and risk management method available. The book is packed with numerous examples using real world data and is supplied with a CD to aid in the use of the examples.

Monte Carlo and Quasi-Monte Carlo Methods 2002 / Proceedings of a Conference held at the National University of Singapore, Republic of Singapore, November 25-28, 2002

Автор: Niederreiter Harald
Название: Monte Carlo and Quasi-Monte Carlo Methods 2002 / Proceedings of a Conference held at the National University of Singapore, Republic of Singapore, November 25-28, 2002
ISBN: 3540204660 ISBN-13(EAN): 9783540204664
Издательство: Springer
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Цена: 19542 р.
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Описание: This book represents the refereed proceedings of the Fifth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at the National University of Singapore in the year 2002. An important feature are invited surveys of the state of the art in key areas such as multidimensional numerical integration, low-discrepancy point sets, computational complexity, finance, and other applications of Monte Carlo and quasi-Monte Carlo methods. These proceedings also include carefully selected contributed papers on all aspects of Monte Carlo and quasi-Monte Carlo methods. The reader will be informed about current research in this very active area.

Random Number Generation and Monte Carlo Methods

Автор: Gentle James E.
Название: Random Number Generation and Monte Carlo Methods
ISBN: 0387001786 ISBN-13(EAN): 9780387001784
Издательство: Springer
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Цена: 7947 р.
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Описание: Surveys techniques of random number generation and the use of random numbers in Monte Carlo simulation. This book covers basic principles, as well as various methods such as parallel random number generation, nonlinear congruential generators, quasi Monte Carlo methods, and Markov chain Monte Carlo.

Rare Event Simulation using Monte Carlo Methods

Автор: Rubino
Название: Rare Event Simulation using Monte Carlo Methods
ISBN: 0470772697 ISBN-13(EAN): 9780470772690
Издательство: Wiley
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Цена: 9875 р.
Наличие на складе: Поставка под заказ.

Описание: Rare events are of critical importance in many areas. For instance, catastrophic failures in transporting systems or in nuclear power plants leading to human losses are represented by rare events, as are money losses through a banks processing / communication system. There are currently journals that include some sections of this subject, but until now no books just one that focuses on just one single methodology (Bucklew). This book will fill that gap in the market, providing a theoretical and implementational guide to various readers; from postgraduates through to engineers, economists, mathematicians, researchers and indeed any person involved or interested in design and simulation. An introductory chapter presents the concept of rare events with areas of application, and then goes on to explain why and when simulation is needed and why standard simulation fails, before describing Monte Carlo and quasi-Monte Carlo simulation. There follows a basic description of the content of the book. After this, the book guides the reader through the Theory section, starting with a chapter  investigating the theoretical properties that estimators should verify as rarity increases (asymptotic efficiency, bounded relative error). We then move on to a chapter on Importance Sampling (General description for the estimation of an integral and of a Markov chain. Some connection with large deviation theory. Zero-variance estimator. Implementation description.) The Theory section of the book is finished with a chapter on Splitting this being a general description of the technique, plus asymptotic results and implementation. The Application section is made up of seven chapters, ranging from Markovian Models for Dependability Analysis, through to Air Traffic Applications and Applications in Biology all seven chapters are written by experts in their fields, something the reviewers have expressed much praise for.  

Monte carlo methods for applied scientists

Автор: Dimov Ivan
Название: Monte carlo methods for applied scientists
ISBN: 9810223293 ISBN-13(EAN): 9789810223298
Издательство: World Scientific Publishing
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Цена: 14571 р.
Наличие на складе: Поставка под заказ.

Описание: The Monte Carlo method is inherently parallel and the extensive and rapid development in vector and parallel computers has resulted in renewed and increasing interest in this method. At the same time there has been an expansion in the application areas and the method is now widely used in many important areas of science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer. This work attempts to bridge the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines.

Although a suitable text for final year or postgraduate mathematicians it is principally aimed at the applied scientists - only a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel algorithm development often to applied industrial problems. Algorithms are developed both for MIMD machines with distributed memory and SIMD machines; a selection of programs are provided.

Monte Carlo Methods, 2nd Edition

Автор: Kalos
Название: Monte Carlo Methods, 2nd Edition
ISBN: 352740760X ISBN-13(EAN): 9783527407606
Издательство: Wiley
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Цена: 12540 р.
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Описание: This is a revised and extended edition of 'Monte Carlo Methods', first published by Wiley in 1986 and still in print (life sales as of 15 Jan. 2007: 3,158 copies). There have been enormous advances in Monte Carlo methods and their applications in the meantime, and the authors propose to bring the treatment up to date while retaining the elementary but general approach.


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