Interface DynamicDataAnalyzer

All Known Implementing Classes:
DynamicDataAnalyzerImpl, NewDynamicDataAnalyzer, QuantileDataAnalyzer
public interface DynamicDataAnalyzer

Title: DynamicDataAnalyzer Interface

Description: This interface is implemented by Data Analyzers used to evaluate confidence intervals and to detect and discard initial transient phase.

Author:
Bertoli Marco Date: 11-gen-2006 Time: 10.40.52

  • Method Summary

    Modifier and Type
    Method
    Description
    boolean
    addSample(double newSample, double weight)
    Adds the new sample to the statistic.
    double
    estimatedMean()
    Gets the estimated mean, even if the confidence requirements have not been reached
    double
    getAlfa()
    Gets measure alpha (i.e.
    double
    getConfInt()
    Gets the half width confidence interval estimated of the monitored data stream.
    int
    getDiscarded()
    Gets the number of discarded data
    double
    getLastIntervalAvg()
    This method return inverse of the instantaneous value
    int
    getMaxData()
    Gets the maximum number of samples that can be analyzed
    double
    getMean()
    Gets the mean estimate of the monitored data stream
    double
    getNullMeasure_upperLimit()
    This method should be called only if mean is equal to zero (@see isZero()), that is when nullTest() returns true.
    double
    getPrecision()
    Gets measure precision (i.e.
    int
    getSamples()
    Gets number of samples elaborated up to now
    boolean
    getSuccess()
    Returns if the analysis was successful
    boolean
    isZero()
    Returns true if null test has found out that this measure is zero
    void
    setParameters(SimParameters parameters)
    Sets the reference to the class containing simulation parameters.
    void
    stopMeasure(boolean success)
    Stops the measuring process

  • Method Details

    • getSuccess

      boolean getSuccess()
      Returns if the analysis was successful
      Returns:
      true if the analysis respect all'users requests

    • getMean

      double getMean()
      Gets the mean estimate of the monitored data stream
      Returns:
      mean estimate of the monitored data stream

    • estimatedMean

      double estimatedMean()
      Gets the estimated mean, even if the confidence requirements have not been reached
      Returns:
      the estimated mean

    • isZero

      boolean isZero()
      Returns true if null test has found out that this measure is zero
      Returns:
      true if null test has found out that this measure is zero

    • getConfInt

      double getConfInt()
      Gets the half width confidence interval estimated of the monitored data stream.
      Returns:
      the confidence interval requested

    • getLastIntervalAvg

      double getLastIntervalAvg()
      This method return inverse of the instantaneous value

    • getNullMeasure_upperLimit

      double getNullMeasure_upperLimit()
      This method should be called only if mean is equal to zero (@see isZero()), that is when nullTest() returns true.
      Returns:
      the upper limit of confidence interval when mean is equal to 0.0

    • getSamples

      int getSamples()
      Gets number of samples elaborated up to now
      Returns:
      number of samples elaborated

    • getDiscarded

      int getDiscarded()
      Gets the number of discarded data
      Returns:
      the number of discarded data

    • getMaxData

      int getMaxData()
      Gets the maximum number of samples that can be analyzed
      Returns:
      maximum number of samples that can be analyzed

    • addSample

      boolean addSample(double newSample, double weight)
      Adds the new sample to the statistic.
      Parameters:
      newSample - the new sample
      weight - the weight of the newSample, if it is not needed put 1.
      Returns:
      true if the computation of confidence interval has finished (i.e. if the confidence interval is smaller than the one required by the user, or if the analyzed data are too many), false otherwise

    • getPrecision

      double getPrecision()
      Gets measure precision (i.e. Maximum relative error)
      Returns:
      precision value

    • getAlfa

      double getAlfa()
      Gets measure alpha (i.e. confidence interval)
      Returns:
      alpha value

    • stopMeasure

      void stopMeasure(boolean success)
      Stops the measuring process
      Parameters:
      success - value to be reported by getSuccess()

    • setParameters

      void setParameters(SimParameters parameters)
      Sets the reference to the class containing simulation parameters. The parameters are updated with the passed values.
      Parameters:
      parameters -