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dc.contributor.authorCano, J. A.-
dc.contributor.authorCarazo, C.-
dc.contributor.authorSalmerón Martínez, Diego-
dc.date.accessioned2025-01-28T11:34:22Z-
dc.date.available2025-01-28T11:34:22Z-
dc.date.issued2016-02-
dc.identifier.citationStatistics and Probability Letters, 2016, vol. 109, pp. 54-62es
dc.identifier.issnPrint: 0167-7152-
dc.identifier.issnElectronic: 1879-2103-
dc.identifier.urihttp://hdl.handle.net/10201/149417-
dc.description© 2015 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is theAccepted version of a Published Work that appeared in final form in Statistics and Probability Letters. To access the final edited and published work see https://doi.org/10.1016/j.spl.2015.11.001es
dc.description.abstractLinear contrasts between means for the one way analysis of variance are studied for the first time as objective model selection problems. For it, Bayes factors for intrinsic priors are used and classical and Bayesian measures of evidence are compared.es
dc.formatapplication/pdfes
dc.format.extent9es
dc.languageenges
dc.publisherElsevieres
dc.relationThis research was supported by the Séneca Foundation Programme for the Generation of Excellence Scientific Knowledge under Project 15220/PI/10.es
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectLinear contrasts between meanses
dc.subjectObjective priorses
dc.subjectBayes factorses
dc.subjectIntrinsic priorses
dc.subjectCalibration curveses
dc.titleLinear contrasts for the one way analysis of variance: a Bayesian approaches
dc.typeinfo:eu-repo/semantics/articlees
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0167715215003740?via%3Dihubes
dc.identifier.doihttps://doi.org/10.1016/j.spl.2015.11.001-
dc.contributor.departmentDepartamento de Ciencias Sociosanitarias-
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