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Robust Bayesian Analysis
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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.
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:
Book Synopsis Robust Bayesian Analysis by : J. O. Berger
Download or read book Robust Bayesian Analysis written by J. O. Berger and published by . This book was released on 1987 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Bayesian Inference when the Data Conflicts with the Prior by : Thomas William Lucas
Download or read book Robust Bayesian Inference when the Data Conflicts with the Prior written by Thomas William Lucas and published by . This book was released on 1991 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Bayesian Analysis by : Yuanzhang Li
Download or read book Robust Bayesian Analysis written by Yuanzhang Li and published by . This book was released on 1990 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
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:
Book Synopsis Robust Bayesian Analysis of Selection Models by : M. J. Bayarri
Download or read book Robust Bayesian Analysis of Selection Models written by M. J. Bayarri and published by . This book was released on 1993 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Bayesian Statistics by : William M. Bolstad
Download or read book Introduction to Bayesian Statistics written by William M. Bolstad and published by John Wiley & Sons. This book was released on 2016-09-02 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: "...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.
Book Synopsis Robust Bayesian Analysis of the Binomial Empirical Bayes Problem by : S. Sivaganesan
Download or read book Robust Bayesian Analysis of the Binomial Empirical Bayes Problem written by S. Sivaganesan and published by . This book was released on 1990 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Bayesian Analysis for Econometrics by : Raffaella Giacomini
Download or read book Robust Bayesian Analysis for Econometrics written by Raffaella Giacomini and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We review the literature on robust Bayesian analysis as a tool for global sensitivity analysis and for statistical decision-making under ambiguity. We discuss the methods proposed in the literature, including the different ways of constructing the set of priors that are the key input of the robust Bayesian analysis. We consider both a general set-up for Bayesian statistical decisions and inference and the special case of set-identified structural models. We provide new results that can be used to derive and compute the set of posterior moments for sensitivity analysis and to compute the optimal statistical decision under multiple priors. The paper ends with a self-contained discussion of three different approaches to robust Bayesian inference for setidentified structural vector autoregressions, including details about numerical implementation and an empirical illustration.
Book Synopsis Discussion of 'An Overview of Robust Bayesian Analysis' by James Berger Self Contained: Original Discussion Not Included by : A. DasGupta
Download or read book Discussion of 'An Overview of Robust Bayesian Analysis' by James Berger Self Contained: Original Discussion Not Included written by A. DasGupta and published by . This book was released on 1994 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Bayesian Analysis and Applications in Linear Models by : Medea Qiuyue Meng
Download or read book Robust Bayesian Analysis and Applications in Linear Models written by Medea Qiuyue Meng and published by . This book was released on 1995 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Global Robust Bayesian Analysis in Large Models by : Paul Ho
Download or read book Global Robust Bayesian Analysis in Large Models written by Paul Ho and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Bayesian Analysis Given Priors on Partition Sets by : Cinzia Carota
Download or read book Robust Bayesian Analysis Given Priors on Partition Sets written by Cinzia Carota and published by . This book was released on 1993 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Robust Bayesian Analysis of Bayesian Networks by : J. Q. Smith
Download or read book The Robust Bayesian Analysis of Bayesian Networks written by J. Q. Smith and published by . This book was released on 2005 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Bayesian Analysis and Optimal Experimental Designs in Normal Linear Models with Many Parameters by : A. DasGupta
Download or read book Robust Bayesian Analysis and Optimal Experimental Designs in Normal Linear Models with Many Parameters written by A. DasGupta and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
