Show simple item record

dc.contributor.authorLee, Youngjo
dc.contributor.authorNelder, J. A.
dc.identifier.citationLee, Youngjo; Nelder, J. A.. "Likelihood for random-effect models (invited article)". SORT, 2005, Vol. 29, núm. 2
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.publisherInstitut d'Estadística de Catalunya
dc.relation.ispartofSORT. 2005, Vol. 29, Núm. 2 [July-December]
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.titleLikelihood for random-effect models (invited article)
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::62 Statistics::62F Parametric inference
dc.rights.accessOpen Access

Files in this item


This item appears in the following Collection(s)

Show simple item record

Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 2.5 Spain