// Toy Monte Carlo example. // Check pull distribution to compare chi2 and binned // log-likelihood methods. void pull( int n_toys = 10000, int n_tot_entries = 100, int nbins = 40, bool do_chi2=true ){ TString method_prefix("Log-Likelihood "); if (do_chi2) method_prefix="#chi^{2} "; // Create histo TH1F h4(method_prefix+"h4", method_prefix+" Random Gauss", nbins,-4,4); h4.SetMarkerStyle(21); h4.SetMarkerSize(0.8); h4.SetMarkerColor(kRed); // Histogram for sigma and pull TH1F sigma(method_prefix+"sigma", method_prefix+"sigma from gaus fit", 50,0.5,1.5); TH1F pull(method_prefix+"pull", method_prefix+"pull from gaus fit", 50,-4.,4.); // Make nice canvases auto c0 = new TCanvas(method_prefix+"Gauss", method_prefix+"Gauss",0,0,320,240); c0->SetGrid(); // Make nice canvases auto c1 = new TCanvas(method_prefix+"Result", method_prefix+"Sigma-Distribution", 0,300,600,400); c0->cd(); float sig, mean; for (int i=0; iGaus()); // perform fit if (do_chi2) h4.Fit("gaus","q"); // Chi2 fit else h4.Fit("gaus","lq"); // Likelihood fit // some control output on the way if (!(i%100)){ h4.Draw("ep"); c0->Update();} // Get sigma from fit TF1 *fit = h4.GetFunction("gaus"); sig = fit->GetParameter(2); mean= fit->GetParameter(1); sigma.Fill(sig); pull.Fill(mean/sig * sqrt(n_tot_entries)); } // end of toy MC loop // print result c1->cd(); pull.DrawClone(); } void macro9(){ int n_toys=10000; int n_tot_entries=100; int n_bins=40; cout << "Performing Pull Experiment with chi2 \n"; pull(n_toys,n_tot_entries,n_bins,true); cout << "Performing Pull Experiment with Log Likelihood\n"; pull(n_toys,n_tot_entries,n_bins,false); }