Selected article for: "growth phase and parameter uncertainty"
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_66
    Snippet: Example #3: Quantifying parameter uncertainty with a negative binomial error structure (see also Example #2) Assuming a negative binomial error structure where the variance is 5 times higher than the mean, we estimate the uncertainty of the r and pparameters of the GGM calibrated to the to the early growth phase of the 2014-16 Ebola epidemic in Sierra Leone. Results are shown in Fig. 9 : 1) the uncertainty of parameters "r" and "p" associated wit.....
    Document: Example #3: Quantifying parameter uncertainty with a negative binomial error structure (see also Example #2) Assuming a negative binomial error structure where the variance is 5 times higher than the mean, we estimate the uncertainty of the r and pparameters of the GGM calibrated to the to the early growth phase of the 2014-16 Ebola epidemic in Sierra Leone. Results are shown in Fig. 9 : 1) the uncertainty of parameters "r" and "p" associated with the fit of the GGM model to the early phase of the Ebola epidemic in Sierra Leone and 2) the 95% confidence bands around the best fit of the model to the data.

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