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dc.contributor.authorOverstall, Antony
dc.contributor.authorKing, Ruth
dc.date.accessioned2013-09-10T14:31:01Z
dc.date.available2013-09-10T14:31:01Z
dc.date.issued2014-01
dc.identifier.citationOverstall , A & King , R 2014 , ' A default prior distribution for contingency tables with dependent factor levels ' , Statistical Methodology , vol. 16 , no. 1 , pp. 90-99 . https://doi.org/10.1016/j.stamet.2013.08.007en
dc.identifier.issn1572-3127
dc.identifier.otherPURE: 28450091
dc.identifier.otherPURE UUID: c6e0e94f-3760-4ad8-8203-b095c4a8abf8
dc.identifier.otherScopus: 84884193116
dc.identifier.otherWOS: 000326555300008
dc.identifier.urihttps://hdl.handle.net/10023/4042
dc.descriptionBoth authors were partly funded by MRC-funded addictions cluster, NIQUAD (Grant No. G1000021).en
dc.description.abstractA default prior distribution is proposed for the Bayesian analysis of contingency tables. The prior is specified to allow for dependence between levels of the factors. Different dependence structures are considered, including conditional autoregressive and distance correlation structures. To demonstrate the prior distribution, a dataset is considered involving estimating the number of injecting drug users in the eleven National Health Service board regions of Scotland using an incomplete contingency table where the dependence structure relates to geographical regions.
dc.format.extent9
dc.language.isoeng
dc.relation.ispartofStatistical Methodologyen
dc.rights© 2014 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.subjectContingency tableen
dc.subjectDependence strustureen
dc.subjectDefault prioren
dc.subjectQA Mathematicsen
dc.subject.lccQAen
dc.titleA default prior distribution for contingency tables with dependent factor levelsen
dc.typeJournal articleen
dc.contributor.sponsorMedical Research Councilen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doihttps://doi.org/10.1016/j.stamet.2013.08.007
dc.description.statusPeer revieweden
dc.identifier.grantnumberPO: MCZ907778en


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