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dc.creatorCarriquiry, Alicia L.es
dc.creatorKliemann, Wolfganges
dc.date2017-04-12
dc.date.accessioned2025-10-06T15:05:07Z
dc.date.available2025-10-06T15:05:07Z
dc.identifierhttps://www.revistaproyecciones.cl/index.php/proyecciones/article/view/1425
dc.identifier10.4067/S0716-09172007000300006
dc.identifier.urihttps://revistaschilenas.uchile.cl/handle/2250/255541
dc.descriptionMixed linear models, also known as two-level hierarchical models, are commonly used in many applications. In this paper, we consider the marginal distribution that arises within a Bayesian framework, when the components of variance are integrated out of the joint posterior distribution. We provide analytical tools for describing the surface of the distribution of interest. The main theorem and its proof show how to determine the number of local maxima, and their approximate location and relative size. This information can be used by practitioners to assess the performance of Laplace-type integral approximations, to compute possibly disconnected highest posterior density regions, and to custom-design numerical algorithms.es
dc.formatapplication/pdf
dc.languagespa
dc.publisherUniversidad Católica del Norte.en
dc.relationhttps://www.revistaproyecciones.cl/index.php/proyecciones/article/view/1425/1212
dc.rightsCopyright (c) 2007 Proyecciones. Journal of Mathematicsen
dc.sourceProyecciones (Antofagasta); Vol. 26 No. 3 (2007); 281-308en
dc.sourceProyecciones. Revista de Matemática; Vol. 26 Núm. 3 (2007); 281-308es
dc.source0717-6279
dc.source10.22199/issn.0717-6279-2007
dc.titleThe modes of posterior distributions for mixed linear modelses
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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