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dc.contributor.authorFreni-Sterrantino, Annaen
dc.contributor.authorVentrucci, Massimoen
dc.contributor.authorRue, Haavarden
dc.date.accessioned2017-12-28T07:32:10Z
dc.date.available2017-12-28T07:32:10Z
dc.date.issued2017-05-13en
dc.identifier.urihttp://hdl.handle.net/10754/626456.1
dc.description.abstractIn this note we discuss (Gaussian) intrinsic conditional autoregressive (CAR) models for disconnected graphs, with the aim of providing practical guidelines for how these models should be defined, scaled and implemented. We show how these suggestions can be implemented in two examples on disease mapping.en
dc.publisherarXiven
dc.relation.urlhttp://arxiv.org/abs/1705.04854v1en
dc.relation.urlhttp://arxiv.org/pdf/1705.04854v1en
dc.rightsArchived with thanks to arXiven
dc.titleA note on intrinsic Conditional Autoregressive models for disconnected graphsen
dc.typePreprinten
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.eprint.versionPre-printen
dc.contributor.institutionSmall Area Health Statistics Unit, Department of Epidemiology and Biostatistics, Imperial College London, United Kingdomen
dc.contributor.institutionDepartment of Statistics, University of Bologna, Bologna, Italyen
dc.identifier.arxividarXiv:1705.04854en
kaust.personRue, Haavard


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