rs_numbercountingutils.C

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/////////////////////////////////////////////////////////////////////////
//
// 'Number Counting Utils' RooStats tutorial 
// author: Kyle Cranmer
// date June. 2009 
//
// This tutorial shows an example of the RooStats standalone 
// utilities that calculate the p-value or Z value (eg. significance in
// 1-sided Gaussian standard deviations) for a number counting experiment.
// This is a hypothesis test between background only and signal-plus-background.
// The background estimate has uncertainty derived from an auxiliary or sideband
// measurement.
//
// Documentation for these utilities can be found here:
// http://root.cern.ch/root/html/RooStats__NumberCountingUtils.html
//
//
// This problem is often called a proto-type problem for high energy physics.
// In some references it is referred to as the on/off problem.
//
// The problem is treated in a fully frequentist fashion by 
// interpreting the relative background uncertainty as
// being due to an auxiliary or sideband observation 
// that is also Poisson distributed with only background.
// Finally, one considers the test as a ratio of Poisson means
// where an interval is well known based on the conditioning on the total
// number of events and the binomial distribution.
// For more on this, see
//  http://arxiv.org/abs/0905.3831
//  http://arxiv.org/abs/physics/physics/0702156
//  http://arxiv.org/abs/physics/0511028
//
/////////////////////////////////////////////////////////////////////////


#ifndef __CINT__
// you need to include this for compiled macro.
// But for CINT, it needs to be in this ifndef/endif condition
#include "RooStats/NumberCountingUtils.h"
#include "RooGlobalFunc.h"
#endif

#include "RooStats/RooStatsUtils.h"

#include <iostream>

using namespace RooFit;
using namespace RooStats ; // the utilities are in the RooStats namespace
using namespace std ;

void rs_numbercountingutils()
{
  
  // From the root prompt, you can see the full list of functions by using tab-completion
  
  // root [0] RooStats::NumberCountingUtils::  <tab>
  // BinomialExpZ
  // BinomialWithTauExpZ
  // BinomialObsZ
  // BinomialWithTauObsZ
  // BinomialExpP
  // BinomialWithTauExpP
  // BinomialObsP
  // BinomialWithTauObsP

  // For each of the utilities you can inspect the arguments by tab completion

  //root [1] NumberCountingUtils::BinomialExpZ( <tab>
  //Double_t BinomialExpZ(Double_t sExp, Double_t bExp, Double_t fractionalBUncertainty)

  /////////////////////////////////////////////////////
  // Here we see common usages where the experimenter
  // has a relative background uncertainty, without
  // explicit reference to the auxiliary or sideband
  // measurement

  /////////////////////////////////////////////////////
  // Expected p-values and significance with background uncertainty
  ////////////////////////////////////////////////////
  double sExpected = 50;
  double bExpected = 100;
  double relativeBkgUncert = 0.1;

  double pExp = NumberCountingUtils::BinomialExpP(sExpected, bExpected, relativeBkgUncert);
  double zExp = NumberCountingUtils::BinomialExpZ(sExpected, bExpected, relativeBkgUncert);
  cout << "expected p-value ="<< pExp << "  Z value (Gaussian sigma) = "<< zExp << endl;

  /////////////////////////////////////////////////////
  // Expected p-values and significance with background uncertainty
  ////////////////////////////////////////////////////
  double observed = 150;
  double pObs = NumberCountingUtils::BinomialObsP(observed, bExpected, relativeBkgUncert);
  double zObs = NumberCountingUtils::BinomialObsZ(observed, bExpected, relativeBkgUncert);
  cout << "observed p-value ="<< pObs << "  Z value (Gaussian sigma) = "<< zObs << endl;


  /////////////////////////////////////////////////////
  // Here we see usages where the experimenter has knowledge
  // about the properties of the auxiliary or sideband
  // measurement.  In particular, the ratio tau of background
  // in the auxiliary measurement to the main measurement.
  // Large values of tau mean small background uncertainty
  // because the sideband is very constraining.
  
  // Usage:
  // root [0] RooStats::NumberCountingUtils::BinomialWithTauExpP( 
  // Double_t BinomialWithTauExpP(Double_t sExp, Double_t bExp, Double_t tau)


  /////////////////////////////////////////////////////
  // Expected p-values and significance with background uncertainty
  ////////////////////////////////////////////////////
  double tau = 1;

  double pExpWithTau = NumberCountingUtils::BinomialWithTauExpP(sExpected, bExpected, tau);
  double zExpWithTau = NumberCountingUtils::BinomialWithTauExpZ(sExpected, bExpected, tau);
  cout << "expected p-value ="<< pExpWithTau << "  Z value (Gaussian sigma) = "<< zExpWithTau << endl;

  /////////////////////////////////////////////////////
  // Expected p-values and significance with background uncertainty
  ////////////////////////////////////////////////////
  double pObsWithTau = NumberCountingUtils::BinomialWithTauObsP(observed, bExpected, tau);
  double zObsWithTau = NumberCountingUtils::BinomialWithTauObsZ(observed, bExpected, tau);
  cout << "observed p-value ="<< pObsWithTau << "  Z value (Gaussian sigma) = "<< zObsWithTau << endl;

}

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