Selected article for: "arima model and province incidence"
Author: Zaixing Shi; Ya Fang
Title: Temporal relationship between outbound traffic from Wuhan and the 2019 coronavirus disease (COVID-19) incidence in China
  • Document date: 2020_3_17
    • ID: hrrzztt5_19
    Snippet: Additionally, we evaluated the potential reduction in the cumulative incidence of COVID-19 cases in other parts of China following the Wuhan travel ban. To account for the variation in the association between traffic volume and COVID-19 incidence by province, we first classified provinces according to their estimated time lag and correlation coefficients using K-means clustering [10] . For each province cluster, we fitted an ARIMA model with traf.....
    Document: Additionally, we evaluated the potential reduction in the cumulative incidence of COVID-19 cases in other parts of China following the Wuhan travel ban. To account for the variation in the association between traffic volume and COVID-19 incidence by province, we first classified provinces according to their estimated time lag and correlation coefficients using K-means clustering [10] . For each province cluster, we fitted an ARIMA model with traffic volume as an external regressor, also known as an ARIMAX model. The ARIMAX model describes the value of at time using the following equations:

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