English(EN) High-dimensional censored MIDAS logistic regression for corporate survival forecasting

新的统计模型应对公司生存预测挑战

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 04:00

研究人员开发了一种新颖的高维审查MIDAS逻辑回归模型来预测公司生存。这种新方法解决了右审查、大量预测变量和混合频率数据等挑战。该方法已在R包Survivalml中实现，为估计误差设定了有限样本界限，并开发了一种去稀疏估计器用于统计推断，同时考虑了审查引起的独特方差结构。 AI

影响该统计模型可以提高商业背景下的财务预测准确性。

排序理由该集群包含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 →

本文如何被排名

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arXiv stat.ML TIER_1 English(EN) · Wei Miao, Jad Beyhum, Jonas Striaukas, Ingrid Van Keilegom · 2026-09-07 04:00

高维审查MIDAS逻辑回归用于公司生存预测

arXiv:2502.09740v3 Announce Type: replace-cross Abstract: This paper addresses the challenge of forecasting corporate distress, a problem marked by three key statistical hurdles: (i) right censoring, (ii) high-dimensional predictors, and (iii) mixed-frequency data. To overcome th…