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dc.contributor.authorCastruccio, Stefano
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2016-01-19T13:20:39Z
dc.date.available2016-01-19T13:20:39Z
dc.date.issued2014-03-13
dc.identifier.citationCastruccio S, Genton MG (2014) Beyond axial symmetry: An improved class of models for global data. Stat 3: 48–55. Available: http://dx.doi.org/10.1002/sta4.44.
dc.identifier.issn2049-1573
dc.identifier.doi10.1002/sta4.44
dc.identifier.urihttp://hdl.handle.net/10754/594063
dc.description.abstractAn important class of models for data on a spherical domain, called axially symmetric, assumes stationarity across longitudes but not across latitudes. The main aim of this work is to introduce a new and more flexible class of models by relaxing the assumption of longitudinal stationarity in the context of regularly gridded climate model output. In this investigation, two other related topics are discussed: the lack of fit of an axially symmetric parametric model compared with a non-parametric model and to longitudinally reversible processes, an important subclass of axially symmetric models.
dc.publisherWiley
dc.subjectAxial symmetry
dc.subjectLongitudinal reversibility
dc.subjectMassive dataset
dc.subjectNon-stationarity
dc.subjectSphere
dc.titleBeyond axial symmetry: An improved class of models for global data
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journalStat
kaust.personCastruccio, Stefano
kaust.personGenton, Marc G.
dc.date.published-online2014-03-13
dc.date.published-print2014-03


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