English(EN) Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection

新的Lasso估计器提高了变量选择效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-15 04:00

研究人员开发了一种广义去偏Lasso估计器，该估计器使用稳定性原理，允许在设计矩阵受到扰动时进行高效更新。在某些亚高斯设计的条件下，这种近似在渐近上是准确的，并简化了条件随机化检验和局部knockoff滤波器等重采样变量选择方法的计算。该方法依赖于集中和反集中论证来管理误差项和符号变化。 AI

影响为统计建模中的变量选择引入了一种更具计算效率的方法。

排序理由这是一篇详细介绍新统计方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv stat.ML TIER_1 English(EN) · Jingbo Liu · 2026-06-15 04:00

具有应用到基于重采样变量选择的广义去偏套索的稳定性

arXiv:2405.03063v3 Announce Type: replace-cross Abstract: We propose a generalized debiased Lasso estimator based on a stability principle. When a single column of the design matrix is perturbed, the estimator admits a simple update formula that can be computed from the original …