TConfidenceLevel

class TConfidenceLevel : public TObject

    public:

                        TConfidenceLevel()
                        TConfidenceLevel(Int_t mc, bool onesided = kTRUE)
                        TConfidenceLevel(const TConfidenceLevel&)
                virtual ~TConfidenceLevel()
         static TClass* Class()
               Double_t CLb(bool use_sMC = kFALSE) const
               Double_t CLs(bool use_sMC = kFALSE) const
               Double_t CLsb(bool use_sMC = kFALSE) const
           virtual void Draw(Option_t* option = "")
               Double_t Get3sProbability() const
               Double_t Get5sProbability() const
               Double_t GetAverageCLs() const
               Double_t GetAverageCLsb() const
               Double_t GetBtot() const
                  Int_t GetDtot() const
               Double_t GetExpectedCLb_b(Int_t sigma = 0) const
               Double_t GetExpectedCLb_sb(Int_t sigma = 0) const
               Double_t GetExpectedCLs_b(Int_t sigma = 0) const
               Double_t GetExpectedCLsb_b(Int_t sigma = 0) const
               Double_t GetExpectedStatistic_b(Int_t sigma = 0) const
               Double_t GetExpectedStatistic_sb(Int_t sigma = 0) const
               Double_t GetStatistic() const
               Double_t GetStot() const
        virtual TClass* IsA() const
      TConfidenceLevel& operator=(const TConfidenceLevel&)
                   void SetBtot(Double_t in)
                   void SetDtot(Int_t in)
                   void SetLRB(Double_t* in)
                   void SetLRS(Double_t* in)
                   void SetStot(Double_t in)
                   void SetTSB(Double_t* in)
                   void SetTSD(Double_t in)
                   void SetTSS(Double_t* in)
           virtual void ShowMembers(TMemberInspector& insp, char* parent)
           virtual void Streamer(TBuffer& b)
                   void StreamerNVirtual(TBuffer& b)

Data Members

    private:

                      Int_t fNNMC      
                      Int_t fDtot      
                   Double_t fStot      
                   Double_t fBtot      
                   Double_t fTSD       
                   Double_t fNMC       
                   Double_t fMCL3S     
                   Double_t fMCL5S     
                  Double_t* fTSB       [fNNMC]
                  Double_t* fTSS       [fNNMC]
                  Double_t* fLRS       [fNNMC]
                  Double_t* fLRB       [fNNMC]
                     Int_t* fISS       [fNNMC]
                     Int_t* fISB       [fNNMC]
      static const Double_t fgMCLM2S   
      static const Double_t fgMCLM1S   
      static const Double_t fgMCLMED   
      static const Double_t fgMCLP1S   
      static const Double_t fgMCLP2S   
      static const Double_t fgMCL3S1S  
      static const Double_t fgMCL5S1S  
      static const Double_t fgMCL3S2S  
      static const Double_t fgMCL5S2S  

 TConfidenceLevel

 Class to compute 95% CL limits

 Default constructor

 a constructor that fix some conventions:
 mc is the number of Monte Carlo experiments
 while onesided specifies if the intervals are one-sided or not.

 The destructor

 Get the expected statistic value in the background only hypothesis

 Get the expected statistic value in the signal plus background hypothesis

 Get the Confidence Level for the background only

 Get the Confidence Level for the signal plus background hypothesis

 Get the Confidence Level defined by CLs = CLsb/CLb.
 This quantity is stable w.r.t. background fluctuations.

 Get the expected Confidence Level for the signal plus background hypothesis
 if there is only background.

 Get the expected Confidence Level for the background only
 if there is signal and background.

 Get the expected Confidence Level for the background only
 if there is only background.

 Get average CLsb.

 Get average CLs.

 Get 3s probability.

 Get 5s probability.

 Display sort of a "canonical" -2lnQ plot.
 This results in a plot with 2 elements:
 - The histogram of -2lnQ for background hypothesis (full)
 - The histogram of -2lnQ for signal and background hypothesis (dashed)
 The 2 histograms are respectively named b_hist and sb_hist.