On nonparametric estimation of the regression function under random censorship model

Guessoum Zohra and Ould-Said Elias
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Guessoum Zohra: Univ. des Sci. et Tech. H. B., Faculté de Mathématiques, El Alia, Algerien

Statistics & Risk Modeling, 2009, vol. 26, issue 3, 159-177

Abstract: In this paper, we study the behavior of a kernel estimator for the regression function in a random right-censoring model. We establish pointwise and uniform strong consistency over a compact set and give a rate of convergence for the estimate.The asymptotic normality of the estimate is also proved. Simulations are drawn for different cases to illustrate both, convergence and asymptotic normality.

Keywords: asymptotic normality; censored data; Kaplan-Meier estimator; kernel; nonparametric regression (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:strimo:v:26:y:2009:i:3:p:159-177:n:2

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DOI: 10.1524/stnd.2008.0919

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