Statistical Modelling 7 (2007), 329–344
Comparison of kernel estimators of conditional distribution function
and quantile regression under censoring
Ali Gannoun
CNAM,
Mathématiques CEDRIC,
France
Jérôme Saracco
Institut de Mathématiques de Bordeaux,
Université Bordeaux 1,
Institut de Mathématiques de Bordeaux,
UMR CNRS 5251,
351 cours de la libération,
F–33405 Talence Cedex
France
and
GREThA,
Université Montesquieu Bordeaux IV,
eMail:
Jerome.Saracco@math.u-bordeaux1.fr
Keming Yu
Department of Mathematical Sciences,
Brunel University,
UK
Abstract:
We consider a regression model in which the variable of interest is
censored. We present various nonparametric estimators of the conditional
distribution function and of conditional quantiles. In a simulation
study, we compare the performance of these estimators. Moreover, the
local linear estimator of conditional quantile is applied on a dataset
dealing with the effect of age on survival time of kidney transplant
patients.
Keywords:
censored data; conditional quantile; kernel estimator;
local linear estimator; survival analysis
Downloads:
Data is available from
http://www.biostat.mcw.edu/homepgs/klein/kidtran.html.
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