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dc.contributorGómez Melis, Guadalupe
dc.contributor.authorGarcía Pareja, Celia
dc.date.accessioned2014-10-23T12:16:42Z
dc.date.issued2014-06
dc.identifier.urihttp://hdl.handle.net/2099.1/23303
dc.description.abstractIn this thesis we propose an estimator for life expectancy based on the idea of partitioning the condi- tional mean of a random variable into different components. Every component of the Compounded Life Expectancy (CLE) estimator represents a fraction of the population of interest and gives a notion of its contribution to the overall life expectancy. Our approach relies on the correspondence between the cumulative distribution function of a random variable and its quantile function, allowing us to express the conditional mean in terms of conditional quantiles. Every component is related to a certain set of quantiles and therefore to a fraction of our population. A method for quantile regression in the presence of censored data is proposed to estimate the underlying conditional quantile function. Results of two simulation studies show a good performance of the proposed estimator under different scenarios.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
dc.subject.lcshSurvival analysis (Biometry)
dc.subject.otherLife expectancy
dc.subject.otherCensoring
dc.subject.otherQuantile regression
dc.titleCompounded life expectancy with randomly censored data
dc.typeMaster thesis
dc.subject.lemacAnàlisi de supervivència (Biometria)
dc.subject.amsClassificació AMS::62 Statistics::62N Survival analysis and censored data
dc.identifier.slugFME-982
dc.rights.accessRestricted access - author's decision
dc.date.lift10000-01-01
dc.date.updated2014-07-02T04:29:46Z
dc.audience.educationlevelMàster
dc.audience.mediatorUniversitat Politècnica de Catalunya. Facultat de Matemàtiques i Estadística
dc.audience.degreeMÀSTER UNIVERSITARI EN ESTADÍSTICA I INVESTIGACIÓ OPERATIVA (Pla 2013)
dc.description.mobilityOutgoing


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