Model: COVID-19 Forecast Hub - COVIDhub-baseline

    Name: baseline
    Abbreviation: COVIDhub-baseline
    Owner: covid19hub
    Team name: COVID-19 Forecast Hub
    Description: This model is a baseline predictive model.
    Contributors: Evan L. Ray <elray@umass.edu>, Ryan Tibshirani
    License: Creative Commons Attribution 4.0
    Notes: secondary
    Citation: Missing
    Methods: For predictions of incidence, the median prediction at all future horizons is the most recent observed incidence. Predictions of cumulative counts are derived from predictions of incidence; this means that the slope of the predictive medians for cumulative quantities from one week to the next will be constant and equal to the last observed slope. To get a distribution around the median, we look at how much incidence has changed from week to week in the past, and we allow for the possibility that similar changes will occur again in the future. In more technical detail, forecasts of incidence are generated through the following procedure: 1) Calculate first differences of incidence; 2) Collect all first differences and their negatives; 3) Sample first differences in incidence and add to the most recent observed incidence; 4) Enforce that the mean of the predictive distribution for incidence is equal to the most recent observed incidence; 5) truncate the predictive distribution for incidence at 0. Forecasts of cumulative quantities are obtained by adding forecasts of incidence to the last observed cumulative value.
    Home: https://covid19forecasthub.org/
    Auxiliary data: https://github.com/reichlab/covidModels

    Forecasts (30)

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