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确定 COVID-19 激增阶段的数据驱动测试方法：警报工具

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY
Statistics Pub Date : 2024-04-02 DOI:10.1080/02331888.2024.2334313
Arianna Agosto, Paola Cerchiello
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引用次数: 0

摘要

对大流行病紧急状况的有效监控，特别是对疫情激增阶段的早期检测，对于制定适当的卫生政策至关重要。我们提出了一种统计检测方法，以...
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A data-driven test approach to identify COVID-19 surge phases: an alert-warning tool
The effective monitoring of the pandemic emergency and, specifically, the early detection of surge phases are crucial to define proper health policies. We propose a statistical testing approach to ...
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来源期刊
Statistics
Statistics 数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍： Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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