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English(EN) Marginal Coordinate Test for Fr\'echet Regression with Random Objects

弗雷歇回归新统计检验方法发布

研究人员开发了一种名为“随机对象弗雷歇回归的边际坐标检验”的新统计检验方法。该检验旨在确定一个预测变量在已考虑其他预测变量的情况下,是否能为响应变量提供额外信息。该方法采用半监督方法,结合标记和未标记数据,并使用核条件均值依赖U统计量。该检验为其零分布、bootstrap有效性和功效建立了理论保证,并包括了同时推断和错误发现率控制的方法。通过模拟和对纽约市出租车数据的分析展示了实际应用。 AI

影响 引入了一种新颖的统计方法,可应用于AI研究中分析复杂数据关系。

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=0.7]

在 arXiv stat.ML 阅读 →

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

弗雷歇回归新统计检验方法发布

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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=0.7]
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完整方法见我们的编辑标准

报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Jiaye Chen, Rui Qiu, Roulin Wang, Zhou Yu ·

    具有随机对象的 Fréchet 回归的边际坐标检验

    arXiv:2608.30644v1 Announce Type: cross Abstract: We develop a marginal coordinate test for regression with Euclidean predictors and a random-object response in a separable metric space. The goal is to test whether a predictor provides additional information about the response co…