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High-dimensional time-varying Aalen and Cox models

Abstract : We consider the problem of estimating the intensity of a counting process in high-dimensional time-varying Aalen and Cox models. We introduce a covariate-specific weighted total-variation penalization, using data-driven weights that correctly scale the penalization along the observation interval. We provide theoretical guaranties for the convergence of our estimators and present a proximal algorithm to solve the convex studied problems. The practical use and effectiveness of the proposed method are demonstrated by simulation studies and real data example.
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Contributor : Agathe Guilloux <>
Submitted on : Monday, June 18, 2018 - 1:04:26 PM
Last modification on : Wednesday, April 8, 2020 - 3:55:43 PM
Document(s) archivé(s) le : Wednesday, September 19, 2018 - 7:35:31 PM


  • HAL Id : hal-01798390, version 1


Mokhtar Z. Alaya, Sarah Lemler, Agathe Guilloux, Thibault Allart. High-dimensional time-varying Aalen and Cox models. 2018. ⟨hal-01798390⟩



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