Nonparametric robust regression estimation for censored data

Mohamed Lemdani () and Elias Ould Saïd ()
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Mohamed Lemdani: Univ. de Lille 2.
Elias Ould Saïd: Univ. Lille Nord de France

Statistical Papers, 2017, vol. 58, issue 2, No 11, 505-525

Abstract: Abstract In this paper, we consider a robust regression estimator when the interest random variable is subject to random right-censoring. Based on the so-called synthetic data, we define a new kernel estimator. Under classical conditions and using a VC-classes theory, we establish its uniform consistency with rate and asymptotic normality properties. Special cases are studied and simulations are drawn to illustrate the main results.

Keywords: Asymptotic normality; Censored data; Kaplan-Meier estimator; Kernel estimator; Robust estimation; Uniform almost sure convergence; Primary 62G20; Secondary 62G07; 62N01; 62E20 (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s00362-015-0709-8

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