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Nonparametric latency estimation for mixture cure models

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URI: http://hdl.handle.net/2183/34590

Publication date

2017-06

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López-Cheda, A., Jácome, M.A. & Cao, R. Nonparametric latency estimation for mixture cure models. TEST 26, 353–376 (2017). https://doi.org/10.1007/s11749-016-0515-1

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Abstract

[Abstract]: A nonparametric latency estimator for mixture cure models is studied in this paper. An i.i.d. representation is obtained, the asymptotic mean squared error of the latency estimator is found, and its asymptotic normality is proven. A bootstrap bandwidth selection method is introduced and its efficiency is evaluated in a simulation study. The proposed methods are applied to a dataset of colorectal cancer patients in the University Hospital of A Coruña (CHUAC).

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This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s11749-016-0515-1

Keywords

Bandwidth selection Bootstrap Censored data Kernel estimation Survival analysis

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https://doi.org/10.1007/s11749-016-0515-1

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Copyright © 2016, Sociedad de Estadística e Investigación Operativa

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