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Article Dans Une Revue Bernoulli Année : 2013

Single index regression models in the presence of censoring depending on the covariates

Résumé

Consider a random vector $(X',Y)'$, where $X$ is $d$-dimensional and $Y$ is one-dimensional. We assume that $Y$ is subject to random right censoring. The aim of this paper is twofold. First we propose a new estimator of the joint distribution of $(X',Y)'$. This estimator overcomes the common curse-of-dimensionality problem, by using a new dimension reduction technique. Second we assume that the relation between $X$ and $Y$ is given by a single index model, and propose a new estimator of the parameters in this model. The asymptotic properties of all proposed estimators are obtained.
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Dates et versions

hal-00644892 , version 1 (25-11-2011)

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Olivier Lopez, Valentin Patilea, Ingrid van Keilegom. Single index regression models in the presence of censoring depending on the covariates. Bernoulli, 2013, 19 (3), pp.721-747. ⟨10.3150/12-BEJ464⟩. ⟨hal-00644892⟩
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