Monte Carlo and Quasi-Monte Carlo Sampling, Christiane Lemieux

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."

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.

Автор: Gamerman, Dani.
Название: Markov Chain Monte Carlo
ISBN: 1584885874 ISBN-13(EAN): 9781584885870
Издательство: Taylor&Francis
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Цена: 15312.00 р.
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Описание: Incorporating changes in theory and highlighting various applications, this book presents a comprehensive introduction to the methods of Markov Chain Monte Carlo (MCMC) simulation technique. It incorporates the developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection.