Public
Edited
Mar 20, 2024
gini = {
var A, B;
B = d3.sum(lorenzCurve.slice(1), (d, i) => (d.x - lorenzCurve[i].x) * d.y);
A = 0.5 - B;
return { A, B, gini: 2 * A };
}
lorenzCurve = {
var x, y, array;
array = wealthPDF.map((d, i) => {
x = d3.sum(wealthPDF.slice(0, i), (d) => d.y);
y = d3.sum(wealthPDF.slice(0, i), (d) => d.x * d.y);
return { x, y };
});
array.map((d) => {
d.x /= x;
d.y /= y;
});
return array;
}
lorenzCurve
Type Table, then Shift-Enter. Ctrl-space for more options.
guess = {
var a, b, c, int, mu, gini;
mu = d3.mean(wealthPDF, (d) => d.x * d.y);
int = d3.sum(joint, (d) => {
a = Math.abs(d.x1 - d.x2);
b = d.y1 * d.y2;
c = d.dx1 * d.dx2;
return a * b * c;
});
gini = int / mu / 2;
return { int, mu, gini };
}
joint = {
var array = [];
wealthPDF.map(({ x: x1, y: y1, dx: dx1 }) => {
wealthPDF.map(({ x: x2, y: y2, dx: dx2 }) => {
array.push({ x1, x2, y1, y2, dx1, dx2 });
});
});
return array;
}
d3.sum(wealthPDF, (d) => d.dx * d.y)
wealthPDF = {
var rndX = d3.randomUniform(1, 2),
scaleY = d3.scaleLinear().domain([-1, 1]).range([0, 1]),
t = fixRandomSeed ? tt.t : getT(),
octave = 10,
array = [];
var x = 0,
dx,
y,
cy = 0;
// Prepare x-axis
for (let i = 0; i < dataResolution; ++i) {
dx = rndX();
x += dx;
array.push({ x, dx });
}
// Simulate raw density
array.map((d) => {
d.x /= x;
d.dx /= x;
d.y = scaleY(noiseGen.noise3D(1, d.x * octave, t));
cy += d.dx * d.y;
d.cy = cy;
});
// Normalize the density: sum(xp(x)) = 1
array.map((d) => {
d.y /= cy;
d.cy /= cy;
});
array.map((d) => (d.x += offsetX));
return array;
}
wealthPDF
Type Table, then Shift-Enter. Ctrl-space for more options.
getT = () => {
var t;
t = performance.now();
Object.assign(tt, { t });
return t;
}
tt = {
return {t: performance.now()};
}
noiseGen.noise3D(1, 2, performance.now() * 1e-5)
noiseGen = new simplexNoise(performance.now())
simplexNoise = require("simplex-noise@2.4.0")
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