The modes of posterior distributions for mixed linear models

dc.contributor.author Carriquiry, Alicia
dc.contributor.author Kliemann, Wolfgang
dc.contributor.author Carriquiry, Alicia
dc.contributor.department Statistics
dc.date 2018-02-17T06:12:13.000
dc.date.accessioned 2020-07-02T06:57:16Z
dc.date.available 2020-07-02T06:57:16Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 2007
dc.date.issued 2007-01-01
dc.description.abstract <p>Mixed 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.</p>
dc.description.comments <p>This article is from <em>Proyecciones</em> 26 (2007): 281, doi:<a href="http://dx.doi.org/%2010.4067/S0716-09172007000300006" target="_blank">10.4067/S0716-09172007000300006</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/22/
dc.identifier.articleid 1020
dc.identifier.contextkey 7849960
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/22
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90532
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/22/2007_CarriquiryAL_ModesPosteriorDistributions.pdf|||Fri Jan 14 22:40:44 UTC 2022
dc.source.uri 10.4067/S0716-09172007000300006
dc.subject.disciplines Statistics and Probability
dc.subject.keywords mixed linear models
dc.subject.keywords posterior modes
dc.subject.keywords poly-t distributions
dc.subject.keywords Pontificia Universidad Catolica de Chile
dc.title The modes of posterior distributions for mixed linear models
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 6ddd5891-2ad0-4a93-89e5-8c35c28b0de4
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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