Interdisciplinary Bayesian Statistics: EBEB 2014
by Lauretto, Marcelo Louzada, Francisco Polpo, Adriano Rifo, Laura L. R. Stern, Julio M.
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 Ana…
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- Full title :Interdisciplinary Bayesian Statistics : EBEB 2014 / edited by Adriano Polpo, Francisco Louzada, Laura L.R. Rifo, Julio M. Stern, Marcelo Lauretto.
Summary
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.
Read More ↓Edition Statements
- Publication Date:2015.
Publication Statements
- Publisher(s):Springer International Publishing
- Place of Publication:Cham
- Language:eng
- Publication Date:2015.
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9783319124544, 3319124544
- oclc:ocn914615180
- LC Classification:QA276-280
- Dewey Decimal:519.5
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