Documentation of 'jhpro.stat.limit.StatConfidence' Java class
StatConfidence
jhpro.stat.limit

Class StatConfidence



  • public class StatConfidence
    extends java.lang.Object
    This is a class to give confidence intervals on various measurements calculated from the number of events observed, the acceptance factor, the background estimate and the associated errors. Results from different experiments (or different channels from the same experiment) can be combined. A complete description is given Computer Physics Communications 149 (2002) 97–102 by Roger Barlow.

    After initializing this class, add data (addData()). Then run "run()" method. You can get probabilities using getProbabilyty method.

    The user can iterate towards whatever limit type they choose, e.g., for a 90% upper limit they adjust the limit guess until the probability is shown as 0.10; for a 90% lower limit they would aim for 0.90.

    • Constructor Summary

      Constructors 
      Constructor and Description
      StatConfidence(double sensitivity, double sigma, double limitguess, int NMCevents)
      Initialize the limit calculations
      StatConfidence(double limitguess, int NMCevents)
      Initialize the limit calculations, assuming efficiency 1.
    • Constructor Detail

      • StatConfidence

        public StatConfidence(double sensitivity,
                              double sigma,
                              double limitguess,
                              int NMCevents)
        Initialize the limit calculations
        Parameters:
        sensitivit - (or efficiency)
        sigma - (uncertainty on efficiency)
        limitguess - initial guess on limit
        NMCevents - Number of Monte Carlo events
      • StatConfidence

        public StatConfidence(double limitguess,
                              int NMCevents)
        Initialize the limit calculations, assuming efficiency 1.
        Parameters:
        limitguess - initial guess on limit
        NMCevents - Number of Monte Carlo events
    • Method Detail

      • addData

        public void addData(ExpData data)
        Add experimental data
        Parameters:
        data - exp data
      • getDataSize

        public void getDataSize()
        Get number of experiments
      • runUpper

        public boolean runUpper()
        Run limit calculations for upper limit. Similar to run(true).
        Returns:
        error
      • runLower

        public boolean runLower()
        Run limit calculations for lower limit. Similar to run(false).
        Returns:
        error
      • run

        public boolean run(boolean isUpper)
        Run limit calculations. You can retrieve probabilities using getProbability* methods. The probabilities depend on guessed limit (which is input).
        Parameters:
        isUpper - set to true for the upper limit. Set to false for the lower limit.
        Returns:
      • getProbabilityCH

        public double getProbabilityCH()
        get probability (Cousins+Highland) for the given limit.
        Returns:
      • getProbabilitySWG

        public double getProbabilitySWG()
        Get probability (BaBar SWG) for the given limit.
        Returns:
      • getProbabilityJ

        public double getProbabilityJ()
        Probability (Jeffreys) for the given limit.
        Returns:
      • setLimitGuess

        public void setLimitGuess(double limitguess)
        Set new limit
        Parameters:
        limitguess -
      • setNMC

        public void setNMC(double NMC)
        Set number of MC events
        Parameters:
        NMC - number of MC events
      • setSensitivity

        public void setSensitivity(double sensitivity)
        Set new sensitivity
        Parameters:
        sensitivity -
      • setSensitivityError

        public void setSensitivityError(double sigma)
        Set error on sensitivity
        Parameters:
        sigma -
      • getLimitGuess

        public double getLimitGuess()
        Get limit guess
        Returns:
      • getNMC

        public double getNMC()
        Get number of MC events
        Returns:
      • getExpData

        public java.util.ArrayList<ExpData> getExpData()
        Get experimental data
        Returns:
      • getSensitivity

        public double getSensitivity()
        Get sensitivity
        Returns:
      • getSensitivityError

        public double getSensitivityError()
        Get error on sensitivity
        Returns:

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