Selected article for: "International license and predictive model"
Author: Maryam Moghadami; Maryam Moghadami; Mohammad Hassanzadeh; ka wa; Aziz Hedayati; Mila Malekolkalami
Title: Modeling the Corona Virus Outbreak in IRAN
  • Document date: 2020_3_27
    • ID: f3qeoyvf_31
    Snippet: The quality of the predictive model for Tehran is acceptable because the dataset is more robust compared to one integrated with seasonality. The Mean Absolute Scaled Error, MASE is less than 1 for the projected 90 days period which is a positive score for the model. The RMSE, unbiased forecast score is slightly higher than the MAE, which gives a median future distribution of 84. The MAPE is over 100% which means the errors are "much greater" then.....
    Document: The quality of the predictive model for Tehran is acceptable because the dataset is more robust compared to one integrated with seasonality. The Mean Absolute Scaled Error, MASE is less than 1 for the projected 90 days period which is a positive score for the model. The RMSE, unbiased forecast score is slightly higher than the MAE, which gives a median future distribution of 84. The MAPE is over 100% which means the errors are "much greater" then the actual values. CC-BY-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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