Warning: Trying to access array offset on false in E:\WWW\html\user.php on line 121 Shinichi Nakajima, Kazuho Watanabe, Masashi Sugiyama Variational Bayesian Learning Theory 9781107076150
Автор: Gelman Название: Bayesian Data Analysis, Third Edition ISBN: 1439840954 ISBN-13(EAN): 9781439840955 Издательство: Taylor&Francis Рейтинг: Цена: 11088.00 р. Наличие на складе: Ожидается поступление.
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.
Описание: Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure.
The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: * Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students.
* Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.
Автор: Gill Название: Bayesian Methods ISBN: 1439862486 ISBN-13(EAN): 9781439862483 Издательство: Taylor&Francis Рейтинг: Цена: 12095.00 р. 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: Donovan Therese Название: Bayesian Statistics for Beginners ISBN: 0198841302 ISBN-13(EAN): 9780198841302 Издательство: Oxford Academ Рейтинг: Цена: 10436.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.
Автор: Richard Michael Cyert Название: Bayesian Analysis and Uncertainty in Economic Theory ISBN: 9401079226 ISBN-13(EAN): 9789401079228 Издательство: Springer Рейтинг: Цена: 10610.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: We were attracted to the Bayesian approach because it seemed the best analytic framework available for dealing with decision making under uncertainty, and the research presented in this book has only served to strengthen our belief in the appropriateness and usefulness of this methodology.
Автор: Jean-Michel Marin; Christian P. Robert Название: Bayesian Essentials with R ISBN: 1493950495 ISBN-13(EAN): 9781493950492 Издательство: Springer Рейтинг: Цена: 7927.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An ideal text for applied statisticians needing a standalone introduction to computational Bayesian statistics, this work by a renowned authority on the subject focuses on standard models backed up by real datasets. It includes an inclusive R (CRAN) package.
Автор: Linden Название: Bayesian Probability Theory ISBN: 1107035902 ISBN-13(EAN): 9781107035904 Издательство: Cambridge Academ Рейтинг: Цена: 14256.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covering all aspects of probability theory, statistics and data analysis from a Bayesian perspective, this book is ideal for graduate students and researchers. It presents the roots, applications and numerical implementation of probability theory, covers advanced topics and features real-world problems.
A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering and economics
The Bayesian Way offers a basic introduction to statistics that emphasizes the Bayesian approach and is designed for use by those studying professional disciplines like engineering and economics. In addition to the Bayesian approach, the author includes the most common techniques of the frequentist approach. Throughout the text, the author covers statistics from a basic to a professional working level along with a practical understanding of the matter at hand.
Filled with helpful illustrations, this comprehensive text explores a wide range of topics, starting with descriptive statistics, set theory, and combinatorics. The text then goes on to review fundamental probability theory and Bayes' theorem. The first part ends in an exposition of stochastic variables, exploring discrete, continuous and mixed probability distributions. In the second part, the book looks at statistical inference. Primarily Bayesian, but with the main frequentist techniques included, it covers conjugate priors through the powerful yet simple method of hyperparameters. It then goes on to topics in hypothesis testing (including utility functions), point and interval estimates (including frequentist confidence intervals), and linear regression. This book:
Explains basic statistics concepts in accessible terms and uses an abundance of illustrations to enhance visual understanding
Has guides for how to calculate the different probability distributions, functions, and statistical properties, on platforms like popular pocket calculators and Mathematica / Wolfram Alpha
Includes example-proofs that enable the reader to follow the reasoning
Contains assignments at different levels of difficulty from simply filling out the correct formula to the complex multi-step text assignments
Offers information on continuous, discrete and mixed probability distributions, hypothesis testing, credible and confidence intervals, and linear regression
Written for undergraduate and graduate students of subjects where Bayesian statistics are applied, including engineering, economics, and related fields, The Bayesian Way: With Applications in Engineering and Economics offers a clear understanding of Bayesian statistics that have real-world applications.
Автор: Marta Blangiardo,Michela Cameletti Название: Spatial and Spatio–temporal Bayesian Models with R – INLA ISBN: 1118326555 ISBN-13(EAN): 9781118326558 Издательство: Wiley Рейтинг: Цена: 9496.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics.
Автор: Barber Название: Bayesian Reasoning and Machine Learning ISBN: 0521518148 ISBN-13(EAN): 9780521518147 Издательство: Cambridge Academ Рейтинг: Цена: 11088.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.
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