Nonparametric estimation of hazard quantile function
P. Sankaran and
N. Unnikrishnan Nair
Journal of Nonparametric Statistics, 2009, vol. 21, issue 6, 757-767
Abstract:
In this paper, we study the estimation of the hazard quantile function based on right censored data. Two nonparametric estimators, one based on the empirical quantile density function and the other using the kernel smoothing method, are proposed. Asymptotic properties of the kernel-based estimator are discussed. Monte Carlo simulation studies are conducted to compare the two estimators. The method is illustrated for a real data set.
Date: 2009
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DOI: 10.1080/10485250902919046
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