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The Dantzig selector in Cox's proportional hazards model

Antoniadis, Anestis, Fryzlewicz, Piotr ORCID: 0000-0002-9676-902X and Letué, Frédérique (2010) The Dantzig selector in Cox's proportional hazards model. Scandinavian Journal of Statistics, 37 (4). pp. 531-552. ISSN 0303-6898

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Identification Number: 10.1111/j.1467-9469.2009.00685.x


The Dantzig selector (DS) is a recent approach of estimation in high-dimensional linear regression models with a large number of explanatory variables and a relatively small number of observations. As in the least absolute shrinkage and selection operator (LASSO), this approach sets certain regression coefficients exactly to zero, thus performing variable selection. However, such a framework, contrary to the LASSO, has never been used in regression models for survival data with censoring. A key motivation of this article is to study the estimation problem for Cox's proportional hazards (PH) function regression models using a framework that extends the theory, the computational advantages and the optimal asymptotic rate properties of the DS to the class of Cox's PH under appropriate sparsity scenarios. We perform a detailed simulation study to compare our approach with other methods and illustrate it on a well-known microarray gene expression data set for predicting survival from gene expressions.

Item Type: Article
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Additional Information: © 2010 John Wiley & Sons
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 20 Dec 2010 13:08
Last Modified: 20 Sep 2021 02:44

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