AI 中文总结
研究如何利用拓扑数据分析中的葡萄园来研究俄亥俄州药物过量流行的时空数据，先提出评估葡萄园适用性的统计测试，后应用于相关数据，合适后用其可视化局部热点演变，并探索验证葡萄园图特征显著性的测试。
AI 中文摘要
理解空间模式如何随时间演变是公共卫生数据分析中的复杂任务。本文通过将拓扑数据分析（TDA）中的葡萄园应用于俄亥俄州药物过量流行的时间序列数据来研究其适用性。首先提出统计测试评估葡萄园是否适用于研究时空数据集，接着将测试应用于俄亥俄州药物过量死亡数据，在数据合适后用葡萄园可视化局部热点演变，最后探索验证葡萄园图特征显著性的统计测试。
英文摘要
Understanding how spatial patterns evolve over time is a complex task that often arises in the analysis of public health data. In this work, we investigate the use of vineyards from topological data analysis (TDA) in this setting by applying them to time series data related to the overdose epidemic in the state of Ohio. We begin by proposing statistical tests that can be used in order to evaluate whether vineyards are a reasonable technique to study a spatiotemporal dataset. We then apply these tests to the data of drug overdose deaths in Ohio and, finding the data suitable, perform a subsequent analysis using vineyards to visualize the evolution of local maxima of death rates throughout the Ohio overdose epidemic. We conclude by developing statistical methods to quantify the significance and uncertainty of vineyard features and by exploring how vineyard-derived summaries can be used for forecasting.
Comments11 pages, 9 figures
