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Bayesian networks and influence diagrams: a guide to construction and analysis, Kjarulff, Uffe B. Madsen, Anders L.


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Цена: 16769.00р.
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Автор: Kjarulff, Uffe B. Madsen, Anders L.
Название:  Bayesian networks and influence diagrams: a guide to construction and analysis
ISBN: 9781461451037
Издательство: Springer
Классификация:





ISBN-10: 1461451035
Обложка/Формат: Hardcover
Страницы: 382
Вес: 0.76 кг.
Дата издания: 29.11.2012
Серия: Information science and statistics
Язык: English
Издание: 2nd ed. 2013
Иллюстрации: 30 tables, black and white; xviii, 382 p.
Размер: 243 x 166 x 30
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: In a Second Edition offering six new sections, new examples, tables, figures and more, this book shows how to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Includes more than 140 examples.


Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

Автор: Uffe B. Kj?rulff; Anders L. Madsen
Название: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
ISBN: 1441925465 ISBN-13(EAN): 9781441925466
Издательство: Springer
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Цена: 10754.00 р.
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Описание: This book provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. The theory and methods presented are illustrated through more than 140 examples.

An Economic Analysis on Automated Construction Safety

Автор: Rita Yi Man Li
Название: An Economic Analysis on Automated Construction Safety
ISBN: 9811057702 ISBN-13(EAN): 9789811057700
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This book addresses information technologies recently applied in the field of construction safety.

Bayesian Data Analysis, Third Edition

Автор: Gelman
Название: Bayesian Data Analysis, Third Edition
ISBN: 1439840954 ISBN-13(EAN): 9781439840955
Издательство: Taylor&Francis
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Цена: 11088.00 р.
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Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Advanced Methodologies for Bayesian Networks

Автор: Joe Suzuki; Maomi Ueno
Название: Advanced Methodologies for Bayesian Networks
ISBN: 3319283782 ISBN-13(EAN): 9783319283784
Издательство: Springer
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Цена: 6708.00 р.
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Описание: This volume constitutes the refereed proceedings of theSecond International Workshop on Advanced Methodologies for Bayesian Networks,AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstractspresented were carefully reviewed and selected from numerous submissions.

Bayesian Networks in Educational Assessment

Автор: Russell G. Almond; Robert J. Mislevy; Linda S. Ste
Название: Bayesian Networks in Educational Assessment
ISBN: 149392124X ISBN-13(EAN): 9781493921249
Издательство: Springer
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Цена: 12577.00 р.
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Описание: Bayesian Networks in Educational Assessment

Bayesian Analysis in Statistics and Econometrics

Автор: Prem K. Goel; N. Sreenivas Iyengar
Название: Bayesian Analysis in Statistics and Econometrics
ISBN: 0387978631 ISBN-13(EAN): 9780387978635
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This volume is based on the invited and the contributed presentations given at the Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics (BASE), Dec. 19-23, 1988, held at the Hotel Taj Residency, Bangalore, India.

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

Автор: Uffe B. Kj?rulff; Anders L. Madsen
Название: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
ISBN: 1493900293 ISBN-13(EAN): 9781493900299
Издательство: Springer
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Цена: 18167.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: In a Second Edition offering six new sections, new examples, tables, figures and more, this book shows how to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Includes more than 140 examples.

Tools and Algorithms for the Construction and Analysis of Systems

Автор: Javier Esparza; Rupak Majumdar
Название: Tools and Algorithms for the Construction and Analysis of Systems
ISBN: 3642120016 ISBN-13(EAN): 9783642120015
Издательство: Springer
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Цена: 12577.00 р.
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Описание: Constitutes the refereed proceedings of the 16th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2010, held in Paphos, Cyprus, in March 2010, as part of ETAPS 2010, the European Joint Conferences on Theory and Practice of Software.

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: 11878.00 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.

Bayesian Analysis of Failure Time Data Using P-Splines

Автор: Matthias Kaeding
Название: Bayesian Analysis of Failure Time Data Using P-Splines
ISBN: 3658083921 ISBN-13(EAN): 9783658083922
Издательство: Springer
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Цена: 9141.00 р.
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Описание: Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions.

Analysis of Images, Social Networks and Texts

Автор: Dmitry I. Ignatov; Mikhail Yu. Khachay; Alexander
Название: Analysis of Images, Social Networks and Texts
ISBN: 3319125796 ISBN-13(EAN): 9783319125794
Издательство: Springer
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Цена: 8106.00 р.
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Описание: This book constitutes the proceedings of the Third International Conference on Analysis of Images, Social Networks and Texts, AIST 2014, held in Yekaterinburg, Russia, in April 2014. They are presented together with 3 short industrial papers, 4 invited papers and tutorials. The papers deal with topics such as analysis of images and videos;

Bayesian Nonparametric Data Analysis

Автор: Peter M?ller; Fernando Andres Quintana; Alejandro
Название: Bayesian Nonparametric Data Analysis
ISBN: 3319368427 ISBN-13(EAN): 9783319368429
Издательство: Springer
Рейтинг:
Цена: 11878.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.


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