rs801_HypoTestInverterOriginal.C File Reference

Detailed Description

An example of using the HypoTestInverterOriginal class

 
 
␛[1mRooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby␛[0m 
                Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
                All rights reserved, please read http://roofit.sourceforge.net/license.txt
 
Target matches upper limit: de-activate interpolation in HypoTestInverterResult
Running for r = 3
Test statistics has been evaluated for data
HybridCalculatorOriginal: run 1000 toy-MC experiments
with test statistics index: 2
....... toy number 0 / 1000
....... toy number 500 / 1000
computed: 0.34252
Running for r = 5
Test statistics has been evaluated for data
HybridCalculatorOriginal: run 1000 toy-MC experiments
with test statistics index: 2
....... toy number 0 / 1000
....... toy number 500 / 1000
computed: 0.0669145
The confidence level at both boundaries are both too large ( 0.34252 and 0.0669145
Run again with other boundaries or larger toy-MC statistics
The computed upper limit is: 5
an estimated error on this upper limit is: 0

 
#include "RooRealVar.h"
#include "RooConstVar.h"
#include "RooProdPdf.h"
#include "RooWorkspace.h"
#include "RooDataSet.h"
#include "RooPolynomial.h"
#include "RooAddPdf.h"
#include "RooExtendPdf.h"
 
#include "RooStats/HypoTestInverterOriginal.h"
#include "RooStats/HypoTestInverterResult.h"
#include "RooStats/HypoTestInverterPlot.h"
#include "RooStats/HybridCalculatorOriginal.h"
 
#include "TGraphErrors.h"
 
using namespace RooFit;
using namespace RooStats;
 
void rs801_HypoTestInverterOriginal()
{
   // prepare the model
   RooRealVar lumi("lumi", "luminosity", 1);
   RooRealVar r("r", "cross-section ratio", 3.74, 0, 50);
   RooFormulaVar ns("ns", "1*r*lumi", RooArgList(lumi, r));
   RooRealVar nb("nb", "background yield", 1);
   RooRealVar x("x", "dummy observable", 0, 1);
   RooConstVar p0(RooFit::RooConst(0));
   RooPolynomial flatPdf("flatPdf", "flat PDF", x, p0);
   RooAddPdf totPdf("totPdf", "S+B model", RooArgList(flatPdf, flatPdf), RooArgList(ns, nb));
   RooExtendPdf bkgPdf("bkgPdf", "B-only model", flatPdf, nb);
   RooDataSet *data = totPdf.generate(x, 1);
 
   // prepare the calculator
   HybridCalculatorOriginal myhc(*data, totPdf, bkgPdf, 0, 0);
   myhc.SetTestStatistic(2);
   myhc.SetNumberOfToys(1000);
   myhc.UseNuisance(false);
 
   // run the hypothesis-test inversion
   HypoTestInverterOriginal myInverter(myhc, r);
   myInverter.SetTestSize(0.10);
   myInverter.UseCLs(true);
   // myInverter.RunFixedScan(5,1,6);
   // scan for a 95% UL
   myInverter.RunAutoScan(3., 5, myInverter.Size() / 2, 0.005);
   // run an alternative autoscan algorithm
   // myInverter.RunAutoScan(1,6,myInverter.Size()/2,0.005,1);
   // myInverter.RunOnePoint(3.9);
 
   HypoTestInverterResult *results = myInverter.GetInterval();
 
   HypoTestInverterPlot myInverterPlot("myInverterPlot", "", results);
   TGraphErrors *gr1 = myInverterPlot.MakePlot();
   gr1->Draw("ALP");
 
   double ulError = results->UpperLimitEstimatedError();
 
   double upperLimit = results->UpperLimit();
   std::cout << "The computed upper limit is: " << upperLimit << std::endl;
   std::cout << "an estimated error on this upper limit is: " << ulError << std::endl;
   // expected result: 4.10
}
int main()
{
   rs801_HypoTestInverterOriginal();
}

Author

Gregory Schott

Definition in file rs801_HypoTestInverterOriginal.C.