Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415647 | Computational Statistics & Data Analysis | 2013 | 14 Pages |
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>np>n, an active-set-type algorithm is proposed. Finally, the method is illustrated with simulation examples and a real microarray study.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Heng Lian, Jianbo Li, Yuao Hu,