Selected article for: "branching process and large number"

Author: de Silva, Eric; Ferguson, Neil M.; Fraser, Christophe
Title: Inferring pandemic growth rates from sequence data
  • Document date: 2012_8_7
  • ID: 1piyoafd_46
    Snippet: Because the problem we have described is that of censoring, and because we are analysing exponentially growing epidemics, we tested whether a parametric (exponential) model improves estimates. We generated a large number of simulated epidemics from three sets of branching process parameters (R ¼ 1.15, k ¼ 10 for.....
    Document: Because the problem we have described is that of censoring, and because we are analysing exponentially growing epidemics, we tested whether a parametric (exponential) model improves estimates. We generated a large number of simulated epidemics from three sets of branching process parameters (R ¼ 1.15, k ¼ 10 for

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