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Non-parametric Quantile Regression with Censored Data
Authors:ALI GANNOUN,JÉ    ME SARACCO,AO YUAN, GEORGE E. BONNEY
Affiliation:UMR CNRS 5149, UniversitéMontpellier II; National Human Genome Center, Howard University
Abstract:
Abstract.  Censored regression models have received a great deal of attention in both the theoretical and applied statistics literature. Here, we consider a model in which the response variable is censored but not the covariates. We propose a new estimator of the conditional quantiles based on the local linear method, and give an algorithm for its numerical implementation. We study its asymptotic properties and evaluate its performance on simulated data sets.
Keywords:censored data    conditional quantiles    Kaplan–Meier estimator    kernel estimator    local linear fitting
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