void exampleFitHistogram() {


   auto h1 = new TH1D("h1","h1",100,-5,5);

   // generate data (gaussian with m=0, s=1)
   h1->FillRandom("gaus");
   // add an extra gaussian contribution (m=0, s= 3)
   for (int i = 0; i < 200; ++i)
      h1->Fill(gRandom->Gaus(0,3));


   auto c1 = new TCanvas();
   c1->Divide(2,1);
   c1->cd(1);

   // fit the data
   TF1 *fitgaus = new TF1("fitgaus", "gaus", -5,5);

   // least square fit
   auto result1 = h1->Fit("fitgaus","S");

   std::cout << " chi2 / " << "ndf = " << result1->Chi2() << " / " << result1->Ndf() << std::endl;

   auto rp1 = new TRatioPlot(h1);
   rp1->Draw();
   h1->SetTitle("Least Square Fit");

   // Maximum likelihood fit
   // copy histogram
   c1->cd(2);

   auto h2 = new TH1D(*h1); 
   h2->SetTitle("Maximum Likelihood Fit");
   auto result2 = h2->Fit("fitgaus","S L");
   // compute chi2 from likelihood ratio (2 * minLL)
   // use all bins (also empty ones) when computing ndf
   std::cout << " chi2 / " << "ndf = " << 2* result2->MinFcnValue() << " / " << result2->Ndf() << std::endl;

   auto rp2 = new TRatioPlot(h2);
   rp2->Draw();

}