Автор: Thompson John Название: Bayesian Analysis with Stata ISBN: 1597181412 ISBN-13(EAN): 9781597181419 Издательство: Taylor&Francis Рейтинг: Цена: 57150.00 T Наличие на складе: Невозможна поставка. 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.
Автор: Richard A. Johnson, Gouri K. Bhattacharyya Название: Statistics: Principles and Methods, 7th Edition ISBN: 0470904119 ISBN-13(EAN): 9780470904114 Издательство: Wiley Рейтинг: Цена: 235790.00 T Наличие на складе: Поставка под заказ. Описание: Statistics: Principles and Methods, 7th Edition provides a comprehensive, accurate introduction to statistics for business professionals who need to learn how to apply key concepts. The chapters include real-world data, designed to make the material more relevant. The numerous examples clearly demonstrate the important points of the methods.
Автор: Gill Название: Bayesian Methods ISBN: 1439862486 ISBN-13(EAN): 9781439862483 Издательство: Taylor&Francis Рейтинг: Цена: 76550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social Scientists
Now that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition focuses more on implementation details of the procedures and less on justifying procedures. The expanded examples reflect this updated approach.
New to the Third Edition
A chapter on Bayesian decision theory, covering Bayesian and frequentist decision theory as well as the connection of empirical Bayes with James-Stein estimation
A chapter on the practical implementation of MCMC methods using the BUGS software
Greatly expanded chapter on hierarchical models that shows how this area is well suited to the Bayesian paradigm
Many new applications from a variety of social science disciplines
Double the number of exercises, with 20 now in each chapter
Updated BaM package in R, including new datasets, code, and procedures for calling BUGS packages from R
This bestselling, highly praised text continues to be suitable for a range of courses, including an introductory course or a computing-centered course. It shows students in the social and behavioral sciences how to use Bayesian methods in practice, preparing them for sophisticated, real-world work in the field.
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 Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Berry, Donald A. Berry, Scott M. Carlin, Bradley P Название: Bayesian adaptive methods for clinical trials ISBN: 1439825483 ISBN-13(EAN): 9781439825488 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis. This book summarizes the state of clinical trial design and analysis and introduces the main ideas and potential benefits of a Bayesian alternative.
Автор: Lesaffre Название: Bayesian Methods in Biostatistics ISBN: 0470018232 ISBN-13(EAN): 9780470018231 Издательство: Wiley Рейтинг: Цена: 59080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: * This book provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementations, with an emphasis on healthcare techniques. * Contains introductory explanations of Bayesian principles common to all areas.
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