Dempster-Shafer P值：关于多项推断替代方法的思考
Dempster-Shafer P-values: Thoughts on an Alternative Approach for Multinomial Inference
AI总结：
本文提出Dempster-Shafer p值作为一种新的证据度量，弥补传统p值不足，并揭示其与频率派检验的联系及在对抗性攻击建模和公共卫生文本分析中的应用。
摘要：
在本文中，我们展示了一种我们开发的新证据度量，称为Dempster-Shafer p值，它能够提供保留p值大部分结构的见解和解释，同时弥补传统p值所面临的一些缺点。此外，我们通过经典的大样本界限和模拟表明，我们的DS假设检验形式与经典频率派检验范式之间存在密切联系。我们还展示了我们的方法如何为假设检验的维度提供独特的见解，以及对多项数据上的对抗性攻击影响进行建模。最后，我们通过对人口健康指标研究联盟（Population Health Metrics Research Consortium）口头尸检数据集的分析，展示了这些见解如何用于分析公共卫生领域的文本数据。
英文摘要：
In this paper, we demonstrate that a new measure of evidence we developed called the Dempster-Shafer p-value which allow for insights and interpretations which retain most of the structure of the p-value while covering for some of the disadvantages that traditional p- values face. Moreover, we show through classical large-sample bounds and simulations that there exists a close connection between our form of DS hypothesis testing and the classical frequentist testing paradigm. We also demonstrate how our approach gives unique insights into the dimensionality of a hypothesis test, as well as models the effects of adversarial attacks on multinomial data. Finally, we demonstrate how these insights can be used to analyze text data for public health through an analysis of the Population Health Metrics Research Consortium dataset for verbal autopsies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
