Logistic curve fitting in epidemiology: Difference between revisions
Logistic curve fitting in epidemiology (view source)
Revision as of 00:06, 29 July 2020
, 3 years ago→{{header|Go}}
Line 207:
r = 0.112302, R0 = 3.84828
</pre>
=={{header|D}}==
{{trans|C++}}
<lang d>import std.math;
import std.stdio;
immutable K = 7.8e9;
immutable n0 = 27;
immutable actual = [
27, 27, 27, 44, 44, 59, 59, 59, 59, 59, 59, 59, 59, 60, 60,
61, 61, 66, 83, 219, 239, 392, 534, 631, 897, 1350, 2023, 2820,
4587, 6067, 7823, 9826, 11946, 14554, 17372, 20615, 24522, 28273,
31491, 34933, 37552, 40540, 43105, 45177, 60328, 64543, 67103,
69265, 71332, 73327, 75191, 75723, 76719, 77804, 78812, 79339,
80132, 80995, 82101, 83365, 85203, 87024, 89068, 90664, 93077,
95316, 98172, 102133, 105824, 109695, 114232, 118610, 125497,
133852, 143227, 151367, 167418, 180096, 194836, 213150, 242364,
271106, 305117, 338133, 377918, 416845, 468049, 527767, 591704,
656866, 715353, 777796, 851308, 928436, 1000249, 1082054, 1174652
];
double f(double r) {
double sq = 0.0;
auto len = actual.length;
for (size_t i = 0; i < len; ++i) {
auto eri = exp(r * i);
auto guess = (n0 * eri) / (1 + n0 * (eri - 1) / K);
auto diff = guess - actual[i];
sq += diff * diff;
}
return sq;
}
double solve(double function(double) fn, double guess = 0.5, double epsilon = 0) {
for (double delta = guess ? guess : 1, f0 = fn(guess), factor = 2;
delta > epsilon && guess != guess - delta;
delta *= factor
) {
double nf = fn(guess - delta);
if (nf < f0) {
f0 = nf;
guess -= delta;
} else {
nf = fn(guess + delta);
if (nf < f0) {
f0 = nf;
guess += delta;
} else {
factor = 0.5;
}
}
}
return guess;
}
void main() {
double r = solve(&f);
double R0 = exp(12 * r);
writeln("r = ", r, ", R0 = ", R0);
}</lang>
{{out}}
<pre>r = 0.112302, R0 = 3.84828</pre>
=={{header|Go}}==
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