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Bayesian Data Analysis, Third Edition, Gelman



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Цена: 12318р.
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Автор: Gelman
Название:  Bayesian Data Analysis, Third Edition
Перевод названия: Джельман: Байесовский анализ данных
ISBN: 9781439840955
Издательство: Taylor&Francis
Издательство: Chapman and Hall/CRC
Классификация:
ISBN-10: 1439840954
Обложка/Формат: Hardback
Страницы: 675
Вес: 1.4 кг.
Дата издания: 05.11.2013
Серия: Chapman & hall/crc texts in statistical science
Язык: English
Издание: 3 revised edition
Иллюстрации: Separate printings at sheridan 49 tables, black and white; 121 illustrations, black and white
Размер: 260 x 178 x 37
Читательская аудитория: General (us: trade)
Ключевые слова: Probability & statistics, MATHEMATICS / Probability & Statistics / General
Ссылка на Издательство: Link
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Поставляется из: Англии



      Старое издание
Bayesian Data Analysis

Автор: Donald B. Rubin
Название: Bayesian Data Analysis
ISBN: 1439898227 ISBN-13(EAN): 9781439898222
Издательство: Неизвестно
Цена: р.
Наличие на складе: Невозможна поставка.


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: 21313 р.
Наличие на складе: Поставка под заказ.

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.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 10036 р.
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Описание: Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks. The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand. Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

Bayesian Methods for Data Analysis, Third Edition

Автор: Carlin
Название: Bayesian Methods for Data Analysis, Third Edition
ISBN: 1584886978 ISBN-13(EAN): 9781584886976
Издательство: Taylor&Francis
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Цена: 9211 р.
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Описание: This proven text provides an accessible introduction to the foundations and applications of Bayesian analysis. Broadening its scope to nonstatisticians, this edition concentrates more on hierarchical Bayesian modeling as implemented via MCMC methods and related data analytic techniques. It contains a reader-friendly introduction to hierarchical statistical modeling, a new chapter on Bayesian design that emphasizes Bayesian clinical trials, a completely revised and expanded section on ranking and histogram estimation, and a new case study on infectious disease modeling and the 1918 flu epidemic. This edition includes new data examples, corresponding R and WinBUGS code, and exercises.

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: 7699 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.

Categorical Data Analysis

Автор: Agresti Alan
Название: Categorical Data Analysis
ISBN: 0470463635 ISBN-13(EAN): 9780470463635
Издательство: Wiley
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Цена: 18970 р.
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Описание: Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis. " Statistics in Medicine "It is a total delight reading this book.

Bayesian Logical Data Analysis for the Physical Sciences

Автор: P. C. Gregory
Название: Bayesian Logical Data Analysis for the Physical Sciences
ISBN: 052184150X ISBN-13(EAN): 9780521841504
Издательство: Cambridge Academ
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Цена: 14791 р.
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Описание: Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. By encompassing both inductive and deductive logic, Bayesian analysis can improve model parameter estimates by many orders of magnitude. It provides a simple and unified approach to all data analysis problems, allowing the experimenter to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. The book also discusses numerical techniques for implementing the Bayesian calculations, including an introduction to Markov Chain Monte-Carlo integration and linear and nonlinear least-squares analysis seen from a Bayesian perspective. In addition, background material is provided in appendices and supporting Mathematica notebooks are available, providing an easy learning route for upper-undergraduates, graduate students, or any serious researcher in physical sciences or engineering.

Bayesian Logical Data Analysis for the Physical Sciences

Автор: Gregory
Название: Bayesian Logical Data Analysis for the Physical Sciences
ISBN: 0521150124 ISBN-13(EAN): 9780521150125
Издательство: Cambridge Academ
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Цена: 7805 р.
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Описание: Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.

Bayesian Analysis of Gene Expression Data

Название: Bayesian Analysis of Gene Expression Data
ISBN: 0470517662 ISBN-13(EAN): 9780470517666
Издательство: Wiley
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Цена: 9350 р.
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Описание: The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinforma

Doing Bayesian Data Analysis,

Автор: John Kruschke
Название: Doing Bayesian Data Analysis,
ISBN: 0124058884 ISBN-13(EAN): 9780124058880
Издательство: Elsevier Science
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Цена: 8201 р.
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Описание: Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes’ rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business.

Bayesian Data Analysis in Ecology Using Linear Models with R, BUG

Автор: Franzi Korner-Nievergelt
Название: Bayesian Data Analysis in Ecology Using Linear Models with R, BUG
ISBN: 0128013702 ISBN-13(EAN): 9780128013700
Издательство: Elsevier Science
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Цена: 7040 р.
Наличие на складе: Поставка под заказ.

Описание: Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data.Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types.

Bayesian Nonparametric Data Analysis

Автор: Muller, P., Quintana, F.A., Jara, A., Hanson, T.
Название: Bayesian Nonparametric Data Analysis
ISBN: 3319189670 ISBN-13(EAN): 9783319189673
Издательство: Springer
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Цена: 9816 р.
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Описание: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.

Analysis of longitudinal data

Название: Analysis of longitudinal data
ISBN: 0199676755 ISBN-13(EAN): 9780199676750
Издательство: Oxford Academ
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Цена: 5887 р.
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Описание: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.


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