| Name: | Historical simplex pattern |
|---|---|
| Abbreviation: | ECDC-soca_simplex |
| Owner: | epiforecasts |
| Team name: | European Centre for Disease Prevention and Control |
| Description: | Using historical data patterns with highest similarity to current data to foreast the future values |
| Contributors: | [{'name': 'Rok Grah', 'affiliation': 'European Centre for Disease Prevention and Control', 'email': 'rok.grah@ecdc.europa.eu'}] |
| License: | Creative Commons Attribution 4.0 |
| Notes: | secondary |
| Citation: | NA |
| Methods: | Model consists of 1) taking 'm' latest data points, 2) find 'n' closest neighbours from all historical data using L2-norm, 3) use the next data time point from each historical data points, 4) use data from point 3 to fit a log-normal distribution , 5) use the log-normal distirbution to estimate the quantiles/distribution, 6) return to step 3 but use two data points ahead for estimations of horizon 2, etc for horizon 3 and 4, 7) find optimal values of 'n' and 'm for a given country, using past 4 weeks of forecasts. |
| Home: | https://www.ecdc.europa.eu/en |
| Auxiliary data: | NA |
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