| Name: | Auto Regressive model with Likelihood Ratio based Model Selection |
|---|---|
| Abbreviation: | ARLR |
| Owner: | (No owner) |
| Team name: | FluX |
| Description: | The method implements an autoregressive model on the weighted ILI time series, and derives a sparse model using a likelihood ratio based model selection. The method is an example of a stepwise regression method with an augmentation phase followed by and a reduction phase, where variables (in this case, lags) are added or removed based on the log-ratio of error term variances with and without the variable. Only producing short-term forecasts through this method, and seasonal forecasts are set to Uniform distribution. Out-of-sample forecasts were generated by using data from Delphi's Epidata API. Missing weeks in early seasons (e.g., EW20-40 for HHS regions before 2014) which were retrospectively filled in 2013EW52, were treated as missing, and filled by linear interpolation. |
| Contributors: | |
| License: | Other License |
| Notes: | |
| Citation: | None |
| Methods: | None |
| Home: | https://github.com/FluSightNetwork/cdc-flusight-ensemble/tree/master/model-forecasts/component-models/FluX_ARLR |
| Auxiliary data: | (No URL) |
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