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

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Lopez, Olivier [Université Pierre et Marie Curie, Paris, France] Patilea, Valentin [CREST (Ensai) et IRMAR, Campus de Ker-Lann, France] Van Keilegom, Ingrid [UCL]

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.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès restreint
Publication date 2013
Language Anglais
Journal information "Bernoulli" - Vol. 19, no. 3, p. 721-747 (2013)
Peer reviewed yes
issn 1350-7265
Publication status Publié
Affiliation UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
Keywords curse-of-dimensionality ; dimension reduction ; multivariate distribution ; right censoring ; semiparametric regression ; survival analysis
Links
Bibliographic reference Lopez, Olivier ; Patilea, Valentin ; Van Keilegom, Ingrid. Single index regression models in the presence of censoring depending on the covariates. In: Bernoulli, Vol. 19, no. 3, p. 721-747 (2013)
Permanent URL http://hdl.handle.net/2078.1/133658