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Title:	Compounded life expectancy with randomly censored data
Author:	García Pareja, Celia
Other authors:	Gómez Melis, Guadalupe
Abstract:	In 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.
Abstract:	Outgoing
Subject(s):	-Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica -Survival analysis (Biometry) -Life expectancy -Censoring -Quantile regression -Anàlisi de supervivència (Biometria) -Classificació AMS::62 Statistics::62N Survival analysis and censored data
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Document type:	Research/Master Thesis
Published by:	Universitat Politècnica de Catalunya
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