ENGLISH

Interdisciplinary Bayesian Statistics: EBEB 2014

By Adriano Polpo de Campos , Francisco Louzada Neto , Laura Ramos Rifo , Julio Michael Stern , Marcelo Lauretto (eds.)

Book information

Publisher
Springer
Year
2015
ISBN
3319124536, 9783319124537, 9783319124544
DOI
10.1007/9783319124544
ISSN
2194-1009
Language
english
Format
PDF
Filesize
9 MB (9109241 bytes)
Series
Springer Proceedings in Mathematics & Statistics 118
Pages
XVIII,366\370
Orientation
portrait
Paginated
yes
Scanned
no
Time added
2015-03-30 18:37:59

Description

Research showcased here comes from international scholars, who presented at EBEB 2014 - XII Brazilian Meeting on Bayesian Statistics Conference and refereed papers here showcase Bayesian Statistics, from theoretical questions to solving problems with real word data EBEB is held by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of ISBA (the International Society for Bayesian Analysis) 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. Content Level » Research Keywords » Bayes' Theorem - Bayesian Statistics - Biostatistics & Clinical Trials - Brazilian chapter ISBA - Imprecise Probability - Microarray Data - Statistical Methodology - Statistical Models in Social Sciences Related subjects » Life Sciences, Medicine & Health - Statistical Theory and Methods - Statistics

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