研究人员开发了一种新的基于矩的回归分析推断方法，该方法利用潜在狄利克雷协变量。该方法解决了使用主题模型输出来作为回归输入时出现的推断挑战，特别是主题估计中的不确定性传播。该方法通过直接识别回归系数来纠正这些问题，而无需估计文档级主题份额，并且还通过算子交换性识别狄利克雷分布的未知总浓度参数。 AI
影响 引入了一种新颖的回归分析统计技术，可能会提高使用主题建模输出的模型的准确性。
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。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2605.30718v1 Announce Type: cross Abstract: Topic models are often used as dimension-reduction tools before regression, with estimated document-level topic shares treated as observed covariates. This plug-in workflow creates two inferential difficulties: valid inference req…
Topic models are often used as dimension-reduction tools before regression, with estimated document-level topic shares treated as observed covariates. This plug-in workflow creates two inferential difficulties: valid inference requires a regular first-stage-to-second-stage expans…