Selected article for: "doubling time and exponential growth"

Author: Janik Schuttler; Reinhard Schlickeiser; Frank Schlickeiser; Martin Kroger
Title: Covid-19 predictions using a Gauss model, based on data from April 2
  • Document date: 2020_4_11
  • ID: 14x9luqu_54
    Snippet: while the doubling time based on D(t) is given by k(t) = (ln 2)/[k ln D(t)/dt] = (ln 2)D(t)/d(t). It is thus easy to calculate two versions of doubling times with the GM parameters at hand, using either daily or total measures, which differ if the growth is not ideally exponential. While doubling times are convenient as they alter only weakly during exponential growth, they are difficult to extract from data directly without applying smoothing pr.....
    Document: while the doubling time based on D(t) is given by k(t) = (ln 2)/[k ln D(t)/dt] = (ln 2)D(t)/d(t). It is thus easy to calculate two versions of doubling times with the GM parameters at hand, using either daily or total measures, which differ if the growth is not ideally exponential. While doubling times are convenient as they alter only weakly during exponential growth, they are difficult to extract from data directly without applying smoothing procedures that differ from publication to publication, and they are not uniquely defined. For this reason we do not recommend to proceed with an analysis on reported doubling times, as done in [13] , unless the raw data is unavailable.

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