{
    using namespace RooFit;

    // Observable
    RooRealVar imass("imass","m [GeV]",105,140);

    // Signal distribution 
    RooRealVar sigmean("sigmean","Resonance mass",115,105,120);
    RooRealVar sigwidth("sigwidth","Resonance width",1,0,4);
    RooGaussian signal("signal","signal PDF",imass,sigmean,sigwidth);

    // Background distribution
    RooRealVar exppar("exppar","Exponential parameter",-.1,-1.,0);
    RooExponential background("background","Exp PDF",imass,exppar);
    
    // Signal plus background distribution
    RooRealVar nsig("nsig","#signal events",150,0.,10000);
    RooRealVar nbkg("nbkg","#background events",1000,0.,10000);
    RooAddPdf model("model","g+a",RooArgList(signal,background),RooArgList(nsig,nbkg));

    // Generate a toy sample according to the expected number of events
    RooDataSet *data = model.generate(imass,Extended());
    
    // ML fit of the model to the data
    model.fitTo(*data);
    
    // Plot everything on a frame
    RooPlot* imassframe = imass.frame();
    data->plotOn(imassframe);
    model.plotOn(imassframe);
        
    model.plotOn(imassframe,Components(background),LineStyle(kDashed));
    
    imassframe->Draw();

    }