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Statistische und Probabilistische Methoden der Modellwahl

dc.date.accessioned2019-10-24T13:11:07Z
dc.date.available2019-10-24T13:11:07Z
dc.date.issued2005
dc.identifier.urihttp://publications.mfo.de/handle/mfo/2921
dc.description.abstractAim of this conference with more than 50 participants, was to bring together leading researchers from roughly three different scientific communities who work on the same issue, data based model selection. Their different methodological approaches can be roughly classified into (1) Frequentist model selection and testing (2) Statistical learning theory and machine learning (3) Bayesian model selection The key task in model selection is to select a proper mathematical model based on information generated by data and/or by prior knowledge. Proper might mean a model with minimal prediction error, a model which describes the main qualitative data features, such as bumps and modes, or a model
dc.titleStatistische und Probabilistische Methoden der Modellwahl
dc.identifier.doi10.14760/OWR-2005-47
local.series.idOWR-2005-47
local.subject.msc62
local.subject.msc60
local.sortindex361
local.date-range16 Oct - 22 Oct 2005
local.workshopcode0542
local.workshoptitleStatistische und Probabilistische Methoden der Modellwahl
local.organizersJames O. Berger, Durham; Holger Dette, Bochum; Gabor Lugosi, Barcelona; Axel Munk, Göttingen
local.report-nameWorkshop Report 2005,47
local.opc-photo-id0542
local.publishers-doi10.4171/OWR/2005/47
local.ems-referenceBerger James, Dette Holger, Lugosi Gabor, Munk Axel: Statistische und Probabilistische Methoden der Modellwahl. Oberwolfach Rep. 2 (2005), 2611-2704. doi: 10.4171/OWR/2005/47


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