Logistic curve fitting in epidemiology: Difference between revisions
Logistic curve fitting in epidemiology (view source)
Revision as of 18:57, 6 April 2020
, 4 years agor vs r0
(Corrected World Population figure in Task description (per Wikipedia) - all 3 existing solutions use this figure anyway.) |
m (r vs r0) |
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Line 147:
const n0 = 27 # starting at day 0 with 27 Chinese cases
""" The model for logistic regression with a given
@. model(t, r) = (n0 * exp(r * t)) / (( 1 + n0 * (exp(r * t) - 1) / K))
Line 192:
n0, K = 27, 7_800_000_000
def f(t,
return (n0 * np.exp(
y = [
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