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Model selection for hazard rate estimation in presence of censoring

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Abstract

This note presents an estimator of the hazard rate function based on right censored data. A collection of estimators is built from a regression-type contrast, in a general collection of linear models. Then, a penalised model selection procedure provides an estimator which satisfies an oracle inequality. In particular, we can prove that it is adaptive in the minimax sense on Hölder spaces.

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Authors and Affiliations

  1. MAP 5 UMR 8145, Université Paris Descartes, 45 rue des Saints Pères, 75006, Paris, France

    Sandra Plancade

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  1. Sandra Plancade
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Correspondence to Sandra Plancade.

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Plancade, S. Model selection for hazard rate estimation in presence of censoring. Metrika 74, 313–347 (2011). https://doi.org/10.1007/s00184-010-0305-9

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  • DOI: https://doi.org/10.1007/s00184-010-0305-9

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