Interdisciplinary Bayesian Statistics

EBEB 2014

Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Science & Nature, Mathematics, Statistics
Cover of the book Interdisciplinary Bayesian Statistics by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319124544
Publisher: Springer International Publishing Publication: February 25, 2015
Imprint: Springer Language: English
Author:
ISBN: 9783319124544
Publisher: Springer International Publishing
Publication: February 25, 2015
Imprint: Springer
Language: English

Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesian methods by the scientific community. Individual papers range in focus from posterior distributions for non-dominated models, to combining optimization and randomization approaches for the design of clinical trials, and classification of archaeological fragments with Bayesian networks.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesian methods by the scientific community. Individual papers range in focus from posterior distributions for non-dominated models, to combining optimization and randomization approaches for the design of clinical trials, and classification of archaeological fragments with Bayesian networks.

More books from Springer International Publishing

Cover of the book Socioeconomic Effects of the National Flood Insurance Program by
Cover of the book Hybrid Metaheuristics by
Cover of the book Road Lighting by
Cover of the book Essentials of Teaching and Integrating Visual and Media Literacy by
Cover of the book Essays on the History of Mechanical Engineering by
Cover of the book Measuring Uncertainty within the Theory of Evidence by
Cover of the book Heavy-Tailed Distributions and Robustness in Economics and Finance by
Cover of the book Information Technologies in Medicine by
Cover of the book Commercial Sexual Exploitation of Children by
Cover of the book Wikipedia, Work and Capitalism by
Cover of the book Bodies and Media by
Cover of the book MediaSync by
Cover of the book Current Developments in Web Based Learning by
Cover of the book General Pontryagin-Type Stochastic Maximum Principle and Backward Stochastic Evolution Equations in Infinite Dimensions by
Cover of the book Toward Predicate Approaches to Modality by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy