Selected article for: "growth model and short term"
Author: Chowell, Gerardo
Title: Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A primer for parameter uncertainty, identifiability, and forecasts
  • Document date: 2017_8_12
    • ID: 3aa8wgr0_92
    Snippet: Fig. 14. The root mean squared errors (RMSE) during the calibration and forecasting intervals using the generalized-growth model (GGM) when the model is fitted to an increasing length of the growth phase (10, 20, …, 80 days) of a synthetic daily incidence curve simulated using the GRM with parameters r ¼ 0:2; p ¼ 0:8; a ¼ 1; and K ¼ 1000. The mean (solid red line) and 95% CIs (dashed red lines) of the RMSE derived from the ensemble curves a.....
    Document: Fig. 14. The root mean squared errors (RMSE) during the calibration and forecasting intervals using the generalized-growth model (GGM) when the model is fitted to an increasing length of the growth phase (10, 20, …, 80 days) of a synthetic daily incidence curve simulated using the GRM with parameters r ¼ 0:2; p ¼ 0:8; a ¼ 1; and K ¼ 1000. The mean (solid red line) and 95% CIs (dashed red lines) of the RMSE derived from the ensemble curves are shown (see Fig. 11 for the corresponding short-term forecasts).

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