Selected article for: "cc NC ND International license and time series"
Author: Pavan Kumar; Himangshu Kalita; Shashikanta Patairiya; Yagya Datt Sharma; Chintan Nanda; Meenu Rani; Jamal Rahmai; Akshaya Srikanth Bhagavathula
Title: Forecasting the dynamics of COVID-19 Pandemic in Top 15 countries in April 2020 through ARIMA Model with Machine Learning Approach
  • Document date: 2020_3_31
    • ID: lxakf79k_4
    Snippet: We used the data of cumulative confirmed death and recovery of COVID-19 cases reported from January 21 until March 26, 2020, that were obtained from John Hopkins Coronavirus resource center (https://coronavirus.jhu.edu/). We analyzed the data using dynamic models to generate 30 days forecasts and to understand the positive effect in the near future as well as projecting trends over trajectories. We used different statistical phenomenological mode.....
    Document: We used the data of cumulative confirmed death and recovery of COVID-19 cases reported from January 21 until March 26, 2020, that were obtained from John Hopkins Coronavirus resource center (https://coronavirus.jhu.edu/). We analyzed the data using dynamic models to generate 30 days forecasts and to understand the positive effect in the near future as well as projecting trends over trajectories. We used different statistical phenomenological models in the R-language platform to analyze the disease-based trajectories model for prediction purposes. We precisely used four models to analyze the aggregate data set for time series analysis. This includes the . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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