English(EN) Cross-Fitted Clipped Covariance Estimation with a Data-Driven Tail-Energy Criterion

新的QTES方法改进了重尾数据的协方差估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员开发了一种名为分位数尾部能量代理（QTES）的新方法，用于估计具有重尾的数据集中的协方差。这种数据驱动的方法旨在优化裁剪级别，在不要求先验分布参数的情况下平衡方差和偏差。实验表明，QTES在干净和污染的重尾数据上表现良好，与现有参考方法相比具有竞争力。 AI

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arXiv stat.ML TIER_1 English(EN) · Even He, Zaizai Yan · 2026-11-02 05:00

Cross-Fitted Clipped Covariance Estimation with a Data-Driven Tail-Energy Criterion

arXiv:2602.14020v2 Announce Type: replace Abstract: Heavy-tailed data make covariance estimation sensitive to the clipping level: stronger clipping reduces variance but increases bias. We study how to choose this clipping level from the data within a radial clipped covariance fam…