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// Compute the ceiling of a / b.
int ceilquot(int a, int b)
{
return (a + b - 1) # b;
}
// Compute the median of a sample.
real getmedian(real[] vals)
{
vals = sort(vals);
int half = quotient(vals.length, 2);
return (vals.length % 2 == 0)
? 0.5 * ( vals[half - 1] + vals[half] ) : vals[half];
return 0;
}
real getmean(real[] vals)
{
return sum(vals) / vals.length;
}
// Bootstrap resampling method for computing the 95% band for the
// median.
real[] mediandev(real[] vals)
{
real[] medlh = new real[3];
int nsample = vals.length;
real resample[] = new real[nsample];
for(int i = 0; i < nsample; ++i) {
resample[i] = vals[i];
}
real median = getmedian(resample);
medlh[0] = median;
// Number of resamples to perform:
int nperm = 2000;
real medians[] = new real[nperm];
for(int i = 0; i < nperm; ++i) {
for(int j = 0; j < nsample; ++j) {
resample[j] = vals[rand() % nsample];
}
medians[i] = getmedian(resample);
}
medians = sort(medians);
real low = medians[(int)floor(nperm * 0.025)];
real high = medians[(int)ceil(nperm * 0.975)];
medlh[1] = low;
medlh[2] = high;
return medlh;
}
real[] ratiodev(real[] vA, real[] vB) {
real[] medlh = new real[2];
real ratio = getmedian(vA) / getmedian(vB);
int nboot = 2000;
real[] ratios =new real[nboot];
ratios[0] = ratio;
for(int n = 1; n < nboot; ++n) {
real valA = vA[rand() % vA.length];
real valB = vB[rand() % vB.length];
ratios[n] = valA / valB;
}
ratios = sort(ratios);
real low = ratios[(int)floor(nboot * 0.025)];
real high = ratios[(int)ceil(nboot * 0.975)];
medlh[0] = low;
medlh[1] = high;
return medlh;
}
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