Kernel Survival Function Estimation Based on Doubly Censored Data

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Kernel_Survival_Function_Estimation_Based_on_Doubl.pdf (540.89 KB)

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https://www.tandfonline.com/doi/full/10.1080/03610920600692748

Permanent Link

https://doi.org/10.1080/03610920600692748
 http://hdl.handle.net/11603/36931

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UMBC Mathematics and Statistics Department

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0001-8594-0568

Date

2006-09-22

Type of Work

journal articles
preprints
Text

Department

Program

Citation of Original Publication

Biswas, Animikh, and Rajeshwari Sundaram. “Kernel Survival Function Estimation Based on Doubly Censored Data.” Communications in Statistics - Theory and Methods 35, no. 7 (June 1, 2006): 1293–1307. https://doi.org/10.1080/03610920600692748.

Rights

This is an original manuscript of an article published by Taylor & Francis in Communications in Statistics - Theory and Methods on 22 Sep 2006, available at: https://doi.org/10.1080/03610920600692748

Subjects

62G08
62G20
62N02
Double censoring
Kernel estimator
Mean integrated squared error

Abstract

This work concerns the estimation of a smooth survival function based on doubly censored data. We establish strong consistency and asymptotic normality for a kernel estimator. Moreover, we also obtain an asymptotic expression for the mean integrated squared error, which yields an optimum bandwidth in terms of readily estimable quantities.