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Logistic curve fitting in epidemiology: Difference between revisions
Logistic curve fitting in epidemiology (view source)
Revision as of 11:57, 7 July 2021
, 2 years ago→{{header|Nim}}
Alextretyak (talk | contribs) (Added 11l) |
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{{out}}
<pre>r = 0.11230217569755005, R0 = 3.8482792809167194</pre>
=={{header|Nim}}==
{{trans|Kotlin}}
<lang Nim>import math, sugar
const
K = 7.8e9
N0 = 27
Actual = [ 27.0, 27.0, 27.0, 44.0, 44.0, 59.0, 59.0,
59.0, 59.0, 59.0, 59.0, 59.0, 59.0, 60.0,
60.0, 61.0, 61.0, 66.0, 83.0, 219.0, 239.0,
392.0, 534.0, 631.0, 897.0, 1350.0, 2023.0, 2820.0,
4587.0, 6067.0, 7823.0, 9826.0, 11946.0, 14554.0, 17372.0,
20615.0, 24522.0, 28273.0, 31491.0, 34933.0, 37552.0, 40540.0,
43105.0, 45177.0, 60328.0, 64543.0, 67103.0, 69265.0, 71332.0,
73327.0, 75191.0, 75723.0, 76719.0, 77804.0, 78812.0, 79339.0,
80132.0, 80995.0, 82101.0, 83365.0, 85203.0, 87024.0, 89068.0,
90664.0, 93077.0, 95316.0, 98172.0, 102133.0, 105824.0, 109695.0,
114232.0, 118610.0, 125497.0, 133852.0, 143227.0, 151367.0, 167418.0,
180096.0, 194836.0, 213150.0, 242364.0, 271106.0, 305117.0, 338133.0,
377918.0, 416845.0, 468049.0, 527767.0, 591704.0, 656866.0, 715353.0,
777796.0, 851308.0, 928436.0, 1000249.0, 1082054.0, 1174652.0]
type Func = (float) -> float
func f(r: float): float =
for i in 0..Actual.high:
let
eri = exp(r * i.toFloat)
guess = (N0 * eri) / (1 + N0 * (eri - 1) / K)
diff = guess - Actual[i]
result += diff * diff
func solve(fn: Func; guess = 0.5, epsilon = 0.0): float =
result = guess
var delta = if result != 0: result else: 1.0
var f0 = fn(result)
var factor = 2.0
while delta > epsilon and result != result - delta:
var nf = fn(result - delta)
if nf < f0:
f0 = nf
result -= delta
else:
nf = fn(result + delta)
if nf < f0:
f0 = nf
result += delta
else:
factor = 0.5
delta *= factor
let r = f.solve()
let r0 = exp(12 * r)
echo "r = ", r, ", R0 = ", r0</lang>
{{out}}
<pre>r = 0.11230217569755, R0 = 3.848279280916719</pre>
=={{header|Perl}}==
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