Evaluating data-driven methods for short-term forecasts of cumulative SARS-CoV2 cases

doi:10.1371/journal.pone.0252147

Svoboda | Graniru | BBC Russia | Golosameriki | Facebook

Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Evaluating data-driven methods for short-term forecasts of cumulative SARS-CoV2 cases

Fig 6

The 4 weeks ahead forecasts for 13 of the 29 countries with the highest cumulative COVID-19 cases and at the aggregated level for the entire world using the ARIMA and ETS methodologies.

doi: https://doi.org/10.1371/journal.pone.0252147.g006