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dc.contributor.authorPosekany, Alexandra
dc.contributor.authorKastner, Gregor
dc.contributor.authorBitto, Angela
dc.contributor.authorFrühwirth-Schnatter, Sylvia
dc.date.accessioned2019-10-26T06:41:37Z
dc.date.available2019-10-26T06:41:37Z
dc.date.created2017-10-28 23:05
dc.date.issued2015
dc.identifieroai:dial.uclouvain.be:ebook:61653
dc.identifierebook:61653
dc.identifierhttp://hdl.handle.net/2078/ebook:61653
dc.identifierinfo:doi/10.1007/978-3-319-16238-6
dc.identifierurn:ISBN:9783319162386
dc.identifier.urihttp://hdl.handle.net/20.500.12424/1642286
dc.description.abstractThe Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session with 30 contributions. Selected contributions have been drawn from the conference for this book. All contributions in this volume are peer-reviewed and share original research in Bayesian computation, application, and theory.
dc.language.isoeng
dc.publisherSpringer International Publishing
dc.subjectEconomics
dc.subjectMathematical statistics
dc.subjectStatistics
dc.subjectQA276
dc.titleBayesian Statistics from Methods to Models and Applications : Research from BAYSM 2014
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ge.dataimportlabelOAI metadata object
ge.identifier.legacyglobethics:11820724
ge.identifier.permalinkhttps://www.globethics.net/gtl/11820724
ge.lastmodificationdate2017-10-28 23:05
ge.lastmodificationuseradmin@pointsoftware.ch (import)
ge.submissions0
ge.oai.exportid149001
ge.oai.repositoryid97999
ge.oai.streamid5
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ge.setspecglobetheolib
ge.linkhttp://hdl.handle.net/2078/ebook:61653


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