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arXiv · 1111.6232

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

Olivier Lopez·Valentin Patilea·Ingrid Van Keilegom
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Abstract

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 mean regression 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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Olivier Lopez, Valentin Patilea, Ingrid Van Keilegom. 2013-09-17. Single index regression models in the presence of censoring depending on the covariates. https://doi.org/10.3150/12-bej464

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