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English(EN) Linear regression with probabilistic networks for network-linked data

新框架使用概率网络对网络链接数据进行建模

研究人员开发了一种分析网络链接数据的新框架,该框架将网络结构与节点观测协变量和响应相结合。这种概率方法明确地模拟了相邻响应之间的依赖性,并考虑了网络形成中的随机性。该方法使用归一化的连接概率来加权同伴响应和潜在位置,以捕捉网络凝聚力,并采用两步法估计网络结构和拟合响应模型。建立了网络恢复和回归估计器一致性的理论保证,并通过模拟和外交网络数据分析展示了其应用。 AI

影响 引入了一种分析复杂网络数据的新型统计方法,有可能在社会科学和网络分析等领域提供更深入的见解。

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]

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 →

新框架使用概率网络对网络链接数据进行建模

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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=0.4]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Jingnan Zhang, Shiwen Ye, Danyang Huang ·

    用于网络链接数据的概率网络线性回归

    arXiv:2610.18937v1 Announce Type: cross Abstract: Network-linked data combine a network with covariates and responses observed for its nodes. Common regression approaches either model dependence among neighboring responses using the observed network or capture similarities associ…