学术报告
报告题目：High-Dimensional Cox Regression With Model Averaging
报 告 人：吴远山 副教授
时 间：2016年3月31日10:40-11：40
地 点：统计研究院426教室
摘要:We propose a model-averaging approach for high-dimensional Cox regression. We choose the weights for the candidate models by using a delete-one cross-validation procedure, which is shown to result in the lowest loss asymptotically. Simulation results demonstrate that the proposed method outperforms the existing methods such as LASSO, SCAD, MCP.
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统计研究院
2016年3月18日