Shrinkage variable selection and estimation in proportional hazards models with additive structure and high dimensionality

Heng Lian, Jianbo Li and Yuao Hu

Computational Statistics & Data Analysis, 2013, vol. 63, issue C, 99-112

Abstract: Variable selection and estimation in proportional hazards models with additive relative risk is considered. Both objectives are achieved using a penalized partial likelihood with a group nonconcave penalty. Oracle properties of the estimator are demonstrated, when the dimensionality is allowed to be larger than sample size. To deal with the computational challenges when p>n, an active-set-type algorithm is proposed. Finally, the method is illustrated with simulation examples and a real microarray study.

Keywords: Akaike information criterion; (Extended) Bayesian information criterion; Polynomial splines; Proportional hazards models (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:63:y:2013:i:c:p:99-112

DOI: 10.1016/j.csda.2013.02.003

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