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dc.contributor.advisorHaslett, John
dc.contributor.authorDillane, Dominic Mark
dc.date.accessioned2019-04-29T15:31:13Z
dc.date.available2019-04-29T15:31:13Z
dc.date.issued2006
dc.identifier.citationDominic Mark Dillane, 'Deletion diagnostics for the linear mixed model', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2006, pp 146
dc.identifier.otherTHESIS 7942
dc.description.abstractModeling data is an integral element of modern statistical analysis. Methodological developments combined with the explosion in computing power over the past ten to fifteen years have greatly enhanced statisticians' ability to model situations and phenomena. The need to assess a model's validity and suitability is an integral element of the model building process. Model criticism is central to this thesis and specifically model criticism for one of the most frequently utilised models in statistical analyses, the Linear Mixed Model with normally distributed errors. Particular emphasis is given to deletion diagnostics for both the fixed and for the covariance structure parameters.
dc.format1 volume
dc.language.isoen
dc.publisherTrinity College (Dublin, Ireland). School of Computer Science & Statistics
dc.relation.isversionofhttp://stella.catalogue.tcd.ie/iii/encore/record/C__Rb12731980
dc.subjectStatistics, Ph.D.
dc.subjectPh.D. Trinity College Dublin
dc.titleDeletion diagnostics for the linear mixed model
dc.typethesis
dc.type.supercollectionthesis_dissertations
dc.type.supercollectionrefereed_publications
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (Ph.D.)
dc.rights.ecaccessrightsopenAccess
dc.format.extentpaginationpp 146
dc.description.noteTARA (Trinity's Access to Research Archive) has a robust takedown policy. Please contact us if you have any concerns: rssadmin@tcd.ie
dc.identifier.urihttp://hdl.handle.net/2262/86289


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