Guided Censored Regression.

Autores: Majda Talamakrouni, Anouar El Ghouch, Ingrid Van Keilegom
Localización: Scandinavian journal of statistics: Theory and applications, ISSN 0303-6898, Vol. 42, Nº. 1, 2015, págs. 214-233
Idioma: inglés
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Resumen
- Parametrically guided non-parametric regression is an appealing method that can reduce the bias of a non-parametric regression function estimator without increasing the variance. In this paper, we adapt this method to the censored data case using an unbiased transformation of the data and a local linear fit. The asymptotic properties of the proposed estimator are established, and its performance is evaluated via finite sample simulations.