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dc.contributor.authorRodríguez-Álvarez, M.X. 
dc.contributor.authorDurban, M.
dc.contributor.authorLee, D.-J. 
dc.contributor.authorEilers, P.H.C.
dc.date.accessioned2018-01-24T17:07:29Z
dc.date.available2018-01-24T17:07:29Z
dc.date.issued2018-01-24
dc.identifier.issn0960-3174
dc.identifier.urihttp://hdl.handle.net/20.500.11824/762
dc.description.abstractWe present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (1977)'s work, but it is able to deal with models that have a precision matrix for the random-effect vector that is linear in the inverse of the variance parameters (i.e., the precision parameters). We call the method SOP (Separation of Overlapping Precision matrices). SOP is based on applying the method of successive approximations to easy-to-compute estimate updates of the variance parameters. These estimate updates have an appealing form: they are the ratio of a (weighted) sum of squares to a quantity related to effective degrees of freedom. We provide the sufficient and necessary conditions for these estimates to be strictly positive. An important application field of SOP is penalised regression estimation of models where multiple quadratic penalties act on the same regression coefficients. We discuss in detail two of those models: penalised splines for locally adaptive smoothness and for hierarchical curve data. Several data examples in these settings are presented.en_US
dc.description.sponsorshipMTM2014-55966-P MTM2014-52184-Pen_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectmixed modelsen_US
dc.subjectpenalised smoothingen_US
dc.subjectoverlapping precision matricesen_US
dc.subjectvariance parameter estimationen_US
dc.titleOn the estimation of variance parameters in non-standard generalised linear mixed models: Application to penalised smoothingen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doi10.1007/s11222-018-9818-2
dc.relation.publisherversionhttps://arxiv.org/submit/2139468en_US
dc.relation.projectIDES/1PE/SEV-2013-0323en_US
dc.relation.projectIDEUS/BERC/BERC.2014-2017en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen_US
dc.journal.titleStatistics and Computingen_US


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Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España