Multidimensional models: normalization and integration of pdfs, construction of cumulative distribution functions from pdfs in two dimensions 
 
  
 
{
   
   
 
   
 
   
 
   
 
   
   
 
   
   cout << 
"gxy = " << 
gxy.getVal() << endl;
 
 
   
   cout << 
"gx_Norm[x,y] = " << 
gxy.getVal(&
nset_xy) << endl;
 
 
   
   
   cout << 
"gx_Int[x,y] = " << 
igxy->getVal() << endl;
 
 
   
 
   
   cout << 
"gx_Norm[x] = " << 
gxy.getVal(&
nset_x) << endl;
 
 
   
   cout << 
"gx_Norm[y] = " << 
gxy.getVal(&
nset_y) << endl;
 
 
   
   
 
   
   x.setRange(
"signal", -5, 5);
 
   y.setRange(
"signal", -3, 3);
 
 
   
   
   
   cout << 
"gx_Int[x,y|signal]_Norm[x,y] = " << 
igxy_sig->getVal() << endl;
 
 
   
   
 
   
   
 
   
 
   new TCanvas(
"rf308_normintegration2d", 
"rf308_normintegration2d", 600, 600);
 
   gPad->SetLeftMargin(0.15);
 
   hh_cdf->GetZaxis()->SetTitleOffset(1.8);
 
}
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
 
RooArgSet is a container object that can hold multiple RooAbsArg objects.
 
Efficient implementation of a product of PDFs of the form.
 
Variable that can be changed from the outside.
 
TH1 is the base class of all histogram classes in ROOT.
 
RooCmdArg YVar(const RooAbsRealLValue &var, const RooCmdArg &arg={})
 
RooCmdArg NormSet(Args_t &&... argsOrArgSet)
 
RooCmdArg Binning(const RooAbsBinning &binning)
 
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
 
   
gxy = 0.485672
gx_Norm[x,y] = 0.0129332
gx_Int[x,y] = 37.5523
gx_Norm[x] = 0.106896
gx_Norm[y] = 0.120989
[#1] INFO:Eval -- RooRealVar::setRange(x) new range named 'signal' created with bounds [-5,5]
[#1] INFO:Eval -- RooRealVar::setRange(y) new range named 'signal' created with bounds [-3,3]
gx_Int[x,y|signal]_Norm[x,y] = 0.572035
- Date
 - July 2008 
 
- Author
 - Wouter Verkerke 
 
Definition in file rf308_normintegration2d.C.