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dc.contributor.authorLee, Youngjo
dc.contributor.authorNelder, J. A.
dc.date.accessioned2007-11-12T19:54:20Z
dc.date.available2007-11-12T19:54:20Z
dc.date.issued2005
dc.identifier.citationLee, Youngjo; Nelder, J. A.. "Likelihood for random-effect models (invited article)". SORT, 2005, Vol. 29, núm. 2
dc.identifier.issn1696-2281
dc.identifier.urihttp://hdl.handle.net/2099/3768
dc.description.abstractHolaFor inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows inference from models that may include both fixed and random parameters. Because of the presence of unobserved random variables h-likelihood is not a likelihood in the Fisherian sense. The Fisher likelihood framework has advantages such as generality of application, statistical and computational efficiency. We introduce an extended likelihood framework and discuss why it is a proper extension, maintaining the advantages of the original likelihood framework. The new framework allows likelihood inferences to be drawn for a much wider class of models.
dc.format.extent141-164
dc.language.isoeng
dc.publisherInstitut d'Estadística de Catalunya
dc.relation.ispartofSORT. 2005, Vol. 29, Núm. 2 [July-December]
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subject.otherInference
dc.titleLikelihood for random-effect models (invited article)
dc.typeArticle
dc.subject.lemacInferència
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::62 Statistics::62F Parametric inference
dc.rights.accessOpen Access


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