using namespace RooFit ;
void one(){
  // C r e a t e   m o d e l   w i t h   p a r a m e t e r   c o n s t r a i n t
  // ---------------------------------------------------------------------------

  // Observable
  RooRealVar x("x","x",-10,10) ;

  // Signal component
  RooRealVar m("m","m",0,-10,10) ;
  RooRealVar s("s","s",2,0.1,10) ;
  RooGaussian g("g","g",x,m,s) ;

  // Background component
  RooPolynomial p("p","p",x) ;

  // Composite model
  RooRealVar f("f","f",0.4,0.,1.) ;
  RooAddPdf sum("sum","sum",RooArgSet(g,p),f) ;

  // S e t u p   t o y   s t u d y   w i t h   m o d e l
  // ---------------------------------------------------

  // Perform toy study
  RooMCStudy mcs(sum,x,Silence(), Extended());

  // Run 500 toys of 2000 events.  
  mcs.generateAndFit(500,2000) ;

  // Make plot of distribution of generated value of f parameter
  TH1* h_f_gen = mcs.fitParDataSet().createHistogram("f",-40) ;

  // Make plot of distribution of fitted value of f parameter
  RooPlot* frame1  = mcs.plotParam(f,Bins(40)) ;
  frame1->SetTitle("Distribution of fitted f values") ;

  TCanvas* c = new TCanvas("c","c",1200,600) ;
  c->Divide(2) ;
  c->cd(1) ; gPad->SetLeftMargin(0.15) ; h_f_gen->GetYaxis()->SetTitleOffset(1.4) ; h_f_gen->Draw() ;
  c->cd(2) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.4) ; frame1->Draw() ;

}