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Bayesian Model Selection and Statistical Modeling, Ando, Tomohiro


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Автор: Ando, Tomohiro
Название:  Bayesian Model Selection and Statistical Modeling
ISBN: 9780367383978
Издательство: Taylor&Francis
Классификация:

ISBN-10: 0367383977
Обложка/Формат: Paperback
Страницы: 300
Вес: 1.22 кг.
Дата издания: 27.09.2019
Язык: English
Размер: 234 x 156 x 16
Читательская аудитория: Tertiary education (us: college)
Основная тема: Statistical Theory & Methods
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation.





The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provides a theoretical basis for the analysis of these criteria. In addition, the author discusses how Bayesian model averaging can simultaneously treat both model and parameter uncertainties.





Selecting and constructing the appropriate statistical model significantly affect the quality of results in decision making, forecasting, stochastic structure explorations, and other problems. Helping you choose the right Bayesian model, this book focuses on the framework for Bayesian model selection and includes practical examples of model selection criteria.




The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Bayesian Modeling Using WinBUGS

Автор: Ntzoufras, Ioannis
Название: Bayesian Modeling Using WinBUGS
ISBN: 047014114X ISBN-13(EAN): 9780470141144
Издательство: Wiley
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Цена: 22168.00 р.
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Описание: Detailed examples will be provided ranging from the very basic to the more advanced; they will also reflect realistic data sets (available from the Internet). An underlying emphasis is given to Generalized Linear Models (GLMs) that are familiar to most readers and researchers.

Statistical Analysis with Missing Data, Third Edit ion

Автор: Little
Название: Statistical Analysis with Missing Data, Third Edit ion
ISBN: 0470526793 ISBN-13(EAN): 9780470526798
Издательство: Wiley
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Цена: 12664.00 р.
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Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.

Subset Selection in Regression

Автор: Miller
Название: Subset Selection in Regression
ISBN: 1584881712 ISBN-13(EAN): 9781584881711
Издательство: Taylor&Francis
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Цена: 27562.00 р.
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Описание: Deals with the techniques for fitting and choosing models that are linear in their parameters and to understanding and correcting the bias introduced by selecting a model. This title includes a chapter on Bayesian methods and an example from the field of near infrared spectroscopy. It emphasises on cross-validation and focuses on bootstrapping.


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