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


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.


Download 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.


Published: August 2013
First available in Project Euclid: 26 June 2013

zbMATH: 1273.62089
MathSciNet: MR3079294
Digital Object Identifier: 10.3150/12-BEJ464

Keywords: curse-of-dimensionality , Dimension reduction , multivariate distribution , right censoring , semiparametric regression , Survival analysis

Rights: Copyright © 2013 Bernoulli Society for Mathematical Statistics and Probability

Vol.19 • No. 3 • August 2013
Back to Top