Local Linear Quantile Regression With Dependent Censored Data. Stat. Sin
AbstractWe consider the problem of nonparametrically estimating the conditional quantile function from censored dependent data. The method proposed here is based on a local linear fit using the check function approach. The asymptotic properties of the proposed estimator are established. Since the estimator is defined as a solution of a minimization problem, we also propose a numerical algorithm. We investigate the performance of the estimator for small samples through a simulation study, and we also discuss the optimal choice of the bandwidth parameters.
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Bibliographic InfoPaper provided by Université catholique de Louvain in its series Open Access publications from Université catholique de Louvain with number info:hdl:2078.1/35141.
Date of creation: 2009
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Publication status: Published in Statistica Sinica (2009) v.19, p.1621-1640
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Web page: http://www.uclouvain.be
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