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dc.contributor.authorWILSON, SIMON PAULen
dc.date.accessioned2010-08-23T10:56:38Z
dc.date.available2010-08-23T10:56:38Z
dc.date.issued2010en
dc.date.submitted2010en
dc.identifier.citationPepa Ramirez Cobo, Rosa E. Lillo, Simon P. Wilson and Michael P. Wiper, Bayesian inference for double Pareto lognormal queues, Annals of Applied Statistics, 4, 3, 2010, 1533 - 1557en
dc.identifier.otherYen
dc.descriptionPUBLISHEDen
dc.description.abstractIn this article we describe a method for carrying out Bayesian inference for the double Pareto lognormal (dPlN) distribution which has recently been proposed as a model for heavy-tailed phenomena. We apply our approach to inference for the dPlN/M/1 and M/dPlN/1 queueing systems. These systems cannot be analyzed using standard techniques due to the fact that the dPlN distribution does not posses a Laplace transform in closed form. This difficulty is overcome using some recent approximations for the Laplace transform for the Pareto/M/1 system. Our procedure is illustrated with applications in internet traffic analysis and risk theory.en
dc.format.extent1533en
dc.format.extent1557en
dc.language.isoenen
dc.relation.ispartofseriesAnnals of Applied Statisticsen
dc.relation.ispartofseries4en
dc.relation.ispartofseries3en
dc.rightsYen
dc.subjectStatistics and probabilityen
dc.subjectBayesian inferenceen
dc.titleBayesian inference for double Pareto lognormal queuesen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/swilsonen
dc.identifier.rssinternalid63353en
dc.identifier.rssurihttp://e-archivo.uc3m.es/bitstream/10016/1316/1/ws080402.pdfen
dc.identifier.urihttp://hdl.handle.net/2262/40572


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