Scalable Sparse Cox's Regression for Large-Scale Survival Data via Broken Adaptive Ridge

This paper develops a new scalable sparse Cox regression tool for sparse high-dimensional massive sample size (sHDMSS) survival data. The method is a local L_0penalized Cox regression via repeatedly performing reweighted L_2penalized Cox regression. We show that the resulting estimator enjoys the best of L_0 and L_2penalized Cox regressions while overcoming their limitations. Specifically, the estimator is selection consistent,...