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dc.contributor.authorDONAGHY, FEARGHALen
dc.date.accessioned2020-02-21T15:39:35Z
dc.date.available2020-02-21T15:39:35Z
dc.date.issued2020en
dc.date.submitted2020en
dc.identifier.citationDONAGHY, FEARGHAL, Modelling the distribution of grouped survival data via dependant neutral-to-the-right priors, Trinity College Dublin.School of Computer Science & Statistics, 2020en
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/91607
dc.descriptionAPPROVEDen
dc.description.abstractWith each update of its browser, Firefox receives reports of the time of discovery of a large number of bugs associated with that update. This process yields survival data which is separated by update into groups and often exhibits much commonality. We propose a model which, rather than treating each group separately, allows for borrowing of information across the entire dataset. To this end, we use superposed completely random measures to construct a vector of dependent neutral-to-the-right priors. The model is completed by accounting for an unobserved number of right-censored data points per group. An explicit characterisation of the posterior distribution of the defined vector of dependent neutral-to-the-right priors is derived and, in turn, used to devise an efficient marginal Markov chain Monte Carlo sampler for posterior inference. A simulation study is carried out to assess the performance of the model. While motivated by the Firefox data, our approach could potentially be useful across a wide range of applications of survival analysis.en
dc.publisherTrinity College Dublin. School of Computer Science & Statistics. Discipline of Statisticsen
dc.rightsYen
dc.subjectcompletely random measuresen
dc.subjectBayesian non-parametricsen
dc.subjectneutral-to-the-right priorsen
dc.subjectBayesian nonparametricsen
dc.subjectsurvival analysisen
dc.subjectMarkov chain Monte Carloen
dc.titleModelling the distribution of grouped survival data via dependant neutral-to-the-right priorsen
dc.typeThesisen
dc.type.supercollectionthesis_dissertationsen
dc.type.supercollectionrefereed_publicationsen
dc.type.qualificationlevelDoctoralen
dc.identifier.peoplefinderurlhttps://tcdlocalportal.tcd.ie/pls/EnterApex/f?p=800:71:0::::P71_USERNAME:DONAGHYFen
dc.identifier.rssinternalid212969en
dc.rights.ecaccessrightsopenAccess


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