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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/180

Title: Bootstrapping quantiles in a fixed design regression model with censored data
Authors: VAN KEILEGOM, Ingrid
Keywords: Mathematical Statistics
Non and semiparametric methods
Issue Date: 1998
Citation: J. Statist. Planning Inf., 69(1). p. 115-131
Abstract: We consider the problem of estimating the quantiles of a distribution function in a fixed design regression model in which the observations are subject to random right censoring. The quantile estimator is defined via a conditional Kaplan-Meier type estimator for the distribution at a given design point. We establish an a.s. asymptotic representation for this quantile estimator, from which we obtain its asymptotic normality. Because a complicated estimation procedure is necessary for estimating the asymptotic bias and variance, we use a resampling procedure, which provides us, via an asymptotic representation for the bootstrapped estimator, with an alternative for the normal approximation
URI: http://hdl.handle.net/1942/180
DOI: 10.1016/S0378-3758(97)00126-2
ISI #: 000074353700009
Type: Journal Contribution
Validation: ecoom, 1999
Appears in Collections: Research publications

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