Selected article for: "control time and time series"

Author: Yueling Ma; Yadong Zhao; Jiangtao Liu; Xiaotao He; Bo Wang; Shihua Fu; Jun Yan; Jingping Niu; Bin Luo
Title: Effects of temperature variation and humidity on the mortality of COVID-19 in Wuhan
  • Document date: 2020_3_18
  • ID: f53i4n02_13
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03. 15.20036426 doi: medRxiv preprint outcomes without including air pollution or weather variables. We incorporated smoothed spline functions of time, which accommodate nonlinear and nonmonotonic patterns between mortality and time, thus offering a flexible modeling tool. Then, we introduced the weather variables and analyzed their effects .....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03. 15.20036426 doi: medRxiv preprint outcomes without including air pollution or weather variables. We incorporated smoothed spline functions of time, which accommodate nonlinear and nonmonotonic patterns between mortality and time, thus offering a flexible modeling tool. Then, we introduced the weather variables and analyzed their effects on mortality. Akaike's information criterion was used as a measure of how well the model fitted the data. Consistent with several recent time-series studies [21, 22] , the penalized smoothing spline function was applied to control the effects of confounding factors, such as time trends, day-of-week and air pollution. The core GAM equation is:

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