Hi Ben,
The fact that there are no entries between 0.8 and 0.9 is simply a
binning artefact. Increase your number of bins from 10 to 100.
The values given to TMath::KolmogorovProv are discrete due to
the difference between consecutive bins (small integers).
Thus introduces an asymmetry in favour of high z values.
Rene Brun
On Thu,
24 Jul 2003, Ben Kilminster wrote:
> Hi fellow Rooters,
>
> The KS probability is supposed to be a value which is uniformly
> distributed between zero and one if you are comparing two distributions
> which come from the same parent distribution.
>
> In the following root macro that I run, I see that it is not flat, it is
> peaked strongly at one, and that there is a big hole where the probability
> is not filled.
>
> Does anyone have any idea what is wrong ?
>
> Cheers,
> Ben
>
> (I am using root v3_05_04d KCC_4_0 Linux+2.4)
>
>
> {
> TCanvas *c1 = new TCanvas("c1","plots",600,700);
> c1->Divide(2,2);
> // Make a gaussian distribution
> TH1F *HGaussMain = new TH1F("HGaussMain","Gaussian pseudoexperiment
> ",100,0,10);
> for (i = 0; i < 10000; i++) {
> HGaussMain->Fill(gRandom->Gaus(5,1.0));
> }
> // Draw the parent distribution
> TCanvas *c1 = new TCanvas("c1","plots",600,700);
> c1->Divide(2,2);
> c1->cd(1);
> HGaussMain->Draw();
>
> // Now loop through choosing 100 event
> // daughter distributions from the parent distribution
> // comparing them with KS statistic
>
> TH1F *HGauss1 = new TH1F("HGauss1","Random Gaussian
> pseudoexperiment",100,0,10);
> TH1F *HGauss2 = new TH1F("HGauss2","Random Gaussian
> pseudoexperiment",100,0,10);
> TH1F *HKSValues = new TH1F("HKSValues","KS values",10,0,1.0);
>
> for (int j = 0; j < 1000; j++) {
> HGauss1->Reset();
> HGauss2->Reset();
> for (int i = 0; i < 100; i++) {
> HGauss1->Fill(HGaussMain->GetRandom());
> HGauss2->Fill(HGaussMain->GetRandom());
> }
> double KS_agree = HGauss1->KolmogorovTest(HGauss2);
> HKSValues->Fill(KS_agree);
> }
>
> c1->cd(2);
> HGauss1->Draw(); // typical daughter distribution
> c1->cd(3);
> HGauss2->Draw(); // another typical daughter distribution
> c1->cd(4);
> HKSValues->Draw(); // This is not flat
>
> }
>
>
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