Bernoulli

  • Bernoulli
  • Volume 19, Number 3 (2013), 721-747.

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

Olivier Lopez, Valentin Patilea, and 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.

Article information

Source
Bernoulli, Volume 19, Number 3 (2013), 721-747.

Dates
First available in Project Euclid: 26 June 2013

Permanent link to this document
https://projecteuclid.org/euclid.bj/1372251141

Digital Object Identifier
doi:10.3150/12-BEJ464

Mathematical Reviews number (MathSciNet)
MR3079294

Zentralblatt MATH identifier
1273.62089

Keywords
curse-of-dimensionality dimension reduction multivariate distribution right censoring semiparametric regression survival analysis

Citation

Lopez, Olivier; Patilea, Valentin; Van Keilegom, Ingrid. Single index regression models in the presence of censoring depending on the covariates. Bernoulli 19 (2013), no. 3, 721--747. doi:10.3150/12-BEJ464. https://projecteuclid.org/euclid.bj/1372251141


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