Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Robustness In The Bayesian Framework full books in PDF, epub, and Kindle. Read online Robustness In The Bayesian Framework ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Mei-Hsiu Ling
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.:/5 (33 download)
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:
Author : David Rios Insua
Publisher : Springer Science & Business Media
ISBN 13 : 1461213061
Total Pages : 431 pages
Book Rating : 4.4/5 (612 download)
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.
Author : Tenglong Li
Publisher :
ISBN 13 : 9780355752991
Total Pages : 165 pages
Book Rating : 4.7/5 (529 download)
Download or read book The Bayesian Paradigm of Robustness Indices of Causal Inferences written by Tenglong Li and published by . This book was released on 2018 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : James O. Berger
Publisher : IMS
ISBN 13 : 9780940600416
Total Pages : 364 pages
Book Rating : 4.6/5 (4 download)
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:
Author : Joseph B. Kadane
Publisher : North Holland
ISBN 13 :
Total Pages : 336 pages
Book Rating : 4.F/5 ( download)
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:
Author : Sang Eun Lee
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.3/5 (121 download)
Download or read book Robustness of Bayesian Factor Analysis Estimates written by Sang Eun Lee and published by . This book was released on 1994 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Andrea Scarinci
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)
Download or read book Robust Bayesian Inference Via Optimal Transport Misfit Measures: Applications and Algorithms written by Andrea Scarinci and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finally, we discuss potential generalizations of TL distances to include the notion of "shape" through time series embeddings, as well as possible extensions of the proposed framework to other forms of model misspecification.
Author : G. E. P. Box
Publisher : Academic Press
ISBN 13 : 1483259390
Total Pages : 317 pages
Book Rating : 4.4/5 (832 download)
Download or read book Scientific Inference, Data Analysis, and Robustness written by G. E. P. Box and published by Academic Press. This book was released on 2014-05-10 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics Research Center Symposium: Scientific Inference, Data Analysis, and Robustness focuses on the philosophy of statistical modeling, including model robust inference and analysis of data sets. The selection first elaborates on pivotal inference and the conditional view of robustness and some philosophies of inference and modeling, including ideas on modeling, significance testing, and scientific discovery. The book then ponders on parametric empirical Bayes confidence intervals, ecumenism in statistics, and frequency properties of Bayes rules. Discussions focus on consistency of Bayes rules, scientific method and the human brain, and statistical estimation and criticism. The book takes a look at the purposes and limitations of data analysis, likelihood, shape, and adaptive inference, statistical inference and measurement of entropy, and the robustness of a hierarchical model for multinomials and contingency tables. Topics include numerical results for contingency tables and robustness, multinomials, flattening constants, and mixed Dirichlet priors, entropy and likelihood, and test as measurement of entropy. The selection is a valuable reference for researchers interested in robust inference and analysis of data sets.
Author : Fabio Cozman
Publisher :
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4.:/5 (382 download)
Download or read book Robustness Analysis of Bayesian Networks with Finitely Generated Convex Sets of Distributions written by Fabio Cozman and published by . This book was released on 1996 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "This paper presents exact solutions and convergent approximations for inferences in Bayesian networks associated with finitely generated convex sets of distributions. Robust Bayesian inference is the calculation of bounds on posterior values given perturbations in a probabilistic model. The paper presents exact inference algorithms and analyzes the circumstances where exact inference becomes intractable. Two classes of algorithms for numeric approximations are developed through transformations on the original model. The first transformation reduces the robust inference problem to the estimation of probabilistic parameters in a Bayesian network. The second transformation uses Lavine's bracketing algorithm to generate a sequence of maximization problems in a Bayesian network. The analysis is extended to the [epsilon]-contaminated, the lower density bounded, the belief function, the sub-sigma, the density bounded, the total variation and the density ratio classes of distributions."
Author : D. V. Lindley
Publisher : SIAM
ISBN 13 : 9780898710021
Total Pages : 100 pages
Book Rating : 4.7/5 (1 download)
Download or read book Bayesian Statistics, A Review written by D. V. Lindley and published by SIAM. This book was released on 1972-01-31 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: A study of those statistical ideas that use a probability distribution over parameter space. The first part describes the axiomatic basis in the concept of coherence and the implications of this for sampling theory statistics. The second part discusses the use of Bayesian ideas in many branches of statistics.
Author : Jochen A. Jungeilges
Publisher : LIT Verlag Münster
ISBN 13 :
Total Pages : 276 pages
Book Rating : 4.X/5 (2 download)
Download or read book The Robustness of Model Selection Rules written by Jochen A. Jungeilges and published by LIT Verlag Münster. This book was released on 1992 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : James Kevin Little
Publisher :
ISBN 13 :
Total Pages : 522 pages
Book Rating : 4.:/5 (89 download)
Download or read book Analysis of the Scale-contaminated Normal Model written by James Kevin Little and published by . This book was released on 1983 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Fabio Cozman
Publisher :
ISBN 13 :
Total Pages : 7 pages
Book Rating : 4.:/5 (382 download)
Download or read book Robustness Analysis of Bayesian Networks with Global Neighborhoods written by Fabio Cozman and published by . This book was released on 1996 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "This paper presents algorithms for robustness analysis of Bayesian networks with global neighborhoods. Robust Bayesian inference is the calculation of bounds on posterior values given perturbations in a probabilistic model. We present algorithms for robust inference (including expected utility, expected value and variance bounds) with global perturbations that can be modeled by [epsilon]-contaminated, constant density ratio, constant density bounded and total variation classes of distributions."
Author : Rosa Mari Fernández Canti
Publisher :
ISBN 13 :
Total Pages : 216 pages
Book Rating : 4.:/5 (112 download)
Download or read book A Bayesian Approach to Robust Identification: Application to Fault Detection written by Rosa Mari Fernández Canti and published by . This book was released on 2013 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the Control Engineering field, the so-called Robust Identification techniques deal with the problem of obtaining not only a nominal model of the plant, but also an estimate of the uncertainty associated to the nominal model. Such model of uncertainty is typically characterized as a region in the parameter space or as an uncertainty band around the frequency response of the nominal model. Uncertainty models have been widely used in the design of robust controllers and, recently, their use in model-based fault detection procedures is increasing. In this later case, consistency between new measurements and the uncertainty region is checked. When an inconsistency is found, the existence of a fault is decided. There exist two main approaches to the modeling of model uncertainty: the deterministic/worst case methods and the stochastic/probabilistic methods. At present, there are a number of different methods, e.g., model error modeling, set-membership identification and non-stationary stochastic embedding. In this dissertation we summarize the main procedures and illustrate their results by means of several examples of the literature. As contribution we propose a Bayesian methodology to solve the robust identification problem. The approach is highly unifying since many robust identification techniques can be interpreted as particular cases of the Bayesian framework. Also, the methodology can deal with non-linear structures such as the ones derived from the use of observers. The obtained Bayesian uncertainty models are used to detect faults in a quadruple-tank process and in a three-bladed wind turbine.
Author : Kuo-Ren Lou
Publisher :
ISBN 13 :
Total Pages : 228 pages
Book Rating : 4.:/5 (356 download)
Download or read book Some Aspects of Bayesian Robustness written by Kuo-Ren Lou and published by . This book was released on 1996 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Thomas Grant Menten
Publisher :
ISBN 13 :
Total Pages : 190 pages
Book Rating : 4.:/5 (634 download)
Download or read book Robustness in Bayesian Inference written by Thomas Grant Menten and published by . This book was released on 1979 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Andrew Gelman
Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.4/5 (398 download)
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.
