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Composite Quantile Regression for Nonparametric Model with Random Censored Data
Department of Mathematics, Tongji University, Shanghai, China
Department of Mathematics, Tongji University, Shanghai, China
- 1 Department of Mathematics, Tongji University, Shanghai, China
- 2 Department of Mathematics, Tongji University, Shanghai, China
Open Journal of Statistics·Volume 03 (2013)·Pages 65–73·Published 16 April 2013·DOI10.4236/ojs.2013.32009
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Abstract
The composite quantile regression should provide estimation efficiency gain over a single quantile regression. In this paper, we extend composite quantile regression to nonparametric model with random censored data. The asymptotic normality of the proposed estimator is established. The proposed methods are applied to the lung cancer data. Extensive simulations are reported, showing that the proposed method works well in practical settings.
KeywordsKaplan-Meier EstimatorCensored DataComposite Quantile RegressionKernel EstimatorNonparametric Model
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