我们集团组织了 3000 多个全球系列会议 每年在美国、欧洲和美国举办的活动亚洲得到 1000 多个科学协会的支持 并出版了 700+ 开放获取期刊包含超过50000名知名人士、知名科学家担任编委会成员。

开放获取期刊获得更多读者和引用
700 种期刊 15,000,000 名读者 每份期刊 获得 25,000 多名读者

抽象的

Linear Regression Analysis of COVID-19 Time-Series Data using the Gumbel Distribution

Hiroshi Furutani, Tomoyuki Hiroyasu

This study uses the Gumbel distribution to model and analyze the daily number of COVID-19 deaths in 8 European and North American countries, as well as in the 7 NHS regions of England, during the first wave of the COVID-19 outbreak. Linear regression is used for parameter estimation and data fitting. The analysis focuses on the height and position of the peak as indicators of the efectiveness of the algorithm. The results of the proposed approach show that the Gumbel model reasonably reproduces the time-series data of COVID-19 deaths in many regions. The advantage of the proposed method is its simplicity and straightforwardness, which allow us to obtain preliminary results for an intuitive image of trends without the need for a sophisticated mathematical framework.

免责声明: 此摘要通过人工智能工具翻译,尚未经过审核或验证。