Robustness In The Bayesian Framework

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Robust Bayesian Analysis

Author : David Rios Insua
Publisher : Springer Science & Business Media
ISBN 13 : 1461213061
Total Pages : 431 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Robust Bayesian Analysis by : David Rios Insua

Download or read book Robust Bayesian Analysis written by David Rios Insua and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust Bayesian analysis aims at overcoming the traditional objection to Bayesian analysis of its dependence on subjective inputs, mainly the prior and the loss. Its purpose is the determination of the impact of the inputs to a Bayesian analysis (the prior, the loss and the model) on its output when the inputs range in certain classes. If the impact is considerable, there is sensitivity and we should attempt to further refine the information the incumbent classes available, perhaps through additional constraints on and/ or obtaining additional data; if the impact is not important, robustness holds and no further analysis and refinement would be required. Robust Bayesian analysis has been widely accepted by Bayesian statisticians; for a while it was even a main research topic in the field. However, to a great extent, their impact is yet to be seen in applied settings. This volume, therefore, presents an overview of the current state of robust Bayesian methods and their applications and identifies topics of further in terest in the area. The papers in the volume are divided into nine parts covering the main aspects of the field. The first one provides an overview of Bayesian robustness at a non-technical level. The paper in Part II con cerns foundational aspects and describes decision-theoretical axiomatisa tions leading to the robust Bayesian paradigm, motivating reasons for which robust analysis is practically unavoidable within Bayesian analysis.

Robustness in the Bayesian Framework

Author : Mei-Hsiu Ling
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.:/5 (33 download)

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Book Synopsis Robustness in the Bayesian Framework by : Mei-Hsiu Ling

Download or read book Robustness in the Bayesian Framework written by Mei-Hsiu Ling and published by . This book was released on 1990 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Robustness

Author : James O. Berger
Publisher : IMS
ISBN 13 : 9780940600416
Total Pages : 364 pages
Book Rating : 4.6/5 (4 download)

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Book Synopsis Bayesian Robustness by : James O. Berger

Download or read book Bayesian Robustness written by James O. Berger and published by IMS. This book was released on 1996 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robustness Tests for Quantitative Research

Author : Eric Neumayer
Publisher : Cambridge University Press
ISBN 13 : 1108415393
Total Pages : 269 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Robustness Tests for Quantitative Research by : Eric Neumayer

Download or read book Robustness Tests for Quantitative Research written by Eric Neumayer and published by Cambridge University Press. This book was released on 2017-08-17 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.

Bayesian Data Analysis, Third Edition

Author : Andrew Gelman
Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman

Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Bayesian Analysis in Statistics and Econometrics

Author : Donald A. Berry
Publisher : John Wiley & Sons
ISBN 13 : 9780471118565
Total Pages : 610 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Bayesian Analysis in Statistics and Econometrics by : Donald A. Berry

Download or read book Bayesian Analysis in Statistics and Econometrics written by Donald A. Berry and published by John Wiley & Sons. This book was released on 1996 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a definitive work that captures the current state of knowledge of Bayesian Analysis in Statistics and Econometrics and attempts to move it forward. It covers such topics as foundations, forecasting inferential matters, regression, computation and applications.

Doing Bayesian Data Analysis

Author : John Kruschke
Publisher : Academic Press
ISBN 13 : 0123814863
Total Pages : 673 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Doing Bayesian Data Analysis by : John Kruschke

Download or read book Doing Bayesian Data Analysis written by John Kruschke and published by Academic Press. This book was released on 2010-11-25 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and 'rusty' calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods. - Accessible, including the basics of essential concepts of probability and random sampling - Examples with R programming language and BUGS software - Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). - Coverage of experiment planning - R and BUGS computer programming code on website - Exercises have explicit purposes and guidelines for accomplishment

Robustness

Author : Lars Peter Hansen
Publisher : Princeton University Press
ISBN 13 : 0691170975
Total Pages : 453 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Robustness by : Lars Peter Hansen

Download or read book Robustness written by Lars Peter Hansen and published by Princeton University Press. This book was released on 2016-06-28 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.

Robustness of Bayesian Analyses

Author : Joseph B. Kadane
Publisher : North Holland
ISBN 13 :
Total Pages : 336 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Robustness of Bayesian Analyses by : Joseph B. Kadane

Download or read book Robustness of Bayesian Analyses written by Joseph B. Kadane and published by North Holland. This book was released on 1984 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robust Diagnostic Regression Analysis

Author : Anthony Atkinson
Publisher : Springer Science & Business Media
ISBN 13 : 1461211603
Total Pages : 342 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Robust Diagnostic Regression Analysis by : Anthony Atkinson

Download or read book Robust Diagnostic Regression Analysis written by Anthony Atkinson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphs are used to understand the relationship between a regression model and the data to which it is fitted. The authors develop new, highly informative graphs for the analysis of regression data and for the detection of model inadequacies. As well as illustrating new procedures, the authors develop the theory of the models used, particularly for generalized linear models. The book provides statisticians and scientists with a new set of tools for data analysis. Software to produce the plots is available on the authors website.

Statistical Rethinking

Author : Richard McElreath
Publisher : CRC Press
ISBN 13 : 1315362619
Total Pages : 488 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Statistical Rethinking by : Richard McElreath

Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Variational Bayesian Learning Theory

Author : Shinichi Nakajima
Publisher : Cambridge University Press
ISBN 13 : 1107076153
Total Pages : 561 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Variational Bayesian Learning Theory by : Shinichi Nakajima

Download or read book Variational Bayesian Learning Theory written by Shinichi Nakajima and published by Cambridge University Press. This book was released on 2019-07-11 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to the theory of variational Bayesian learning summarizes recent developments and suggests practical applications.

Bayesian Statistics and Marketing

Author : Peter E. Rossi
Publisher : John Wiley & Sons
ISBN 13 : 0470863684
Total Pages : 368 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Bayesian Statistics and Marketing by : Peter E. Rossi

Download or read book Bayesian Statistics and Marketing written by Peter E. Rossi and published by John Wiley & Sons. This book was released on 2012-05-14 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources. Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods. Written by the leading experts in the field, this unique book: Presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models. Provides a self-contained introduction to Bayesian methods. Includes case studies drawn from the authors’ recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems. Is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition the book’s website hosts datasets and R code for the case studies. Bayesian Statistics and Marketing provides a platform for researchers in marketing to analyse their data with state-of-the-art methods and develop new models of consumer behaviour. It provides a unified reference for cutting-edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.

Robust Monitoring, Diagnostic Methods and Tools for Engineered Systems

Author : Eleni N. Chatzi
Publisher : Frontiers Media SA
ISBN 13 : 2889660885
Total Pages : 208 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Robust Monitoring, Diagnostic Methods and Tools for Engineered Systems by : Eleni N. Chatzi

Download or read book Robust Monitoring, Diagnostic Methods and Tools for Engineered Systems written by Eleni N. Chatzi and published by Frontiers Media SA. This book was released on 2020-10-23 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Informative Hypotheses

Author : Herbert Hoijtink
Publisher : CRC Press
ISBN 13 : 1439880514
Total Pages : 243 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Informative Hypotheses by : Herbert Hoijtink

Download or read book Informative Hypotheses written by Herbert Hoijtink and published by CRC Press. This book was released on 2011-10-26 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: When scientists formulate their theories, expectations, and hypotheses, they often use statements like: ``I expect mean A to be bigger than means B and C"; ``I expect that the relation between Y and both X1 and X2 is positive"; and ``I expect the relation between Y and X1 to be stronger than the relation between Y and X2". Stated otherwise, they formulate their expectations in terms of inequality constraints among the parameters in which they are interested, that is, they formulate Informative Hypotheses. There is currently a sound theoretical foundation for the evaluation of informative hypotheses using Bayes factors, p-values and the generalized order restricted information criterion. Furthermore, software that is often free is available to enable researchers to evaluate the informative hypotheses using their own data. The road is open to challenge the dominance of the null hypothesis for contemporary research in behavioral, social, and other sciences.

Bayesian Modeling and Computation in Python

Author : Osvaldo A. Martin
Publisher : CRC Press
ISBN 13 : 1000520048
Total Pages : 420 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Bayesian Modeling and Computation in Python by : Osvaldo A. Martin

Download or read book Bayesian Modeling and Computation in Python written by Osvaldo A. Martin and published by CRC Press. This book was released on 2021-12-28 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory. The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics. This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries.

Handbook of Robust Low-Rank and Sparse Matrix Decomposition

Author : Thierry Bouwmans
Publisher : CRC Press
ISBN 13 : 1498724639
Total Pages : 553 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Handbook of Robust Low-Rank and Sparse Matrix Decomposition by : Thierry Bouwmans

Download or read book Handbook of Robust Low-Rank and Sparse Matrix Decomposition written by Thierry Bouwmans and published by CRC Press. This book was released on 2016-05-27 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.