Abstract In this article, we propose model-free marginal and conditional feature screening approaches for ultra-high dimensional competing risks data. The suggested procedures possess ranking consistency and sure screening properties. Their finite-sample performances are verified through numerical studies.

中文翻译：

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超高维竞争风险数据的无模型特征筛选

摘要 在本文中，我们提出了用于超高维竞争风险数据的无模型边缘和条件特征筛选方法。建议的程序具有排序一致性和确定的筛选特性。它们的有限样本性能通过数值研究得到验证。