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.
Citation
Olivier Lopez. Valentin Patilea. Ingrid Van Keilegom. "Single index regression models in the presence of censoring depending on the covariates." Bernoulli 19 (3) 721 - 747, August 2013. https://doi.org/10.3150/12-BEJ464
Information