Package org.djutils.stats.summarizers.event

Class EventBasedTally

java.lang.Object
org.djutils.event.EventProducer
org.djutils.stats.summarizers.event.EventBasedTally
All Implemented Interfaces:
Serializable, EventListener, org.djutils.event.EventListenerInterface, org.djutils.event.EventProducerInterface, BasicTallyInterface, TallyInterface
public class EventBasedTally
extends org.djutils.event.EventProducer
implements org.djutils.event.EventListenerInterface, TallyInterface
The EventBasedTally class ingests a series of values and provides mean, standard deviation, etc. of the ingested values. It extends an EventProducer so it can keep listeners informed about new observations, and it listens to external events to be able to receive observations, in addition to the ingest(...) method.

Copyright (c) 2002-2020 Delft University of Technology, Jaffalaan 5, 2628 BX Delft, the Netherlands. All rights reserved. See for project information https://simulation.tudelft.nl. The DSOL project is distributed under a three-clause BSD-style license, which can be found at https://simulation.tudelft.nl/dsol/3.0/license.html.

Author:
Alexander Verbraeck, Peter Jacobs , Peter Knoppers
See Also:
Serialized Form

  • Field Summary

    Fields inherited from class org.djutils.event.EventProducer

    eventProducerImpl

    Fields inherited from interface org.djutils.event.EventProducerInterface

    FIRST_POSITION, LAST_POSITION

  • Constructor Summary

    Constructors 
    Constructor Description
    EventBasedTally​(String description)
    Convenience constructor that uses a NoStorageAccumulator to estimate quantiles.
    EventBasedTally​(String description, QuantileAccumulator quantileAccumulator)
    Constructs a new EventBasedTally.

  • Method Summary

    Modifier and Type Method Description
    protected void fireEvents()
    Method that can be overridden to fire own events or additional events when ingesting an observation.
    double[] getConfidenceInterval​(double alpha)
    returns the confidence interval on either side of the mean.
    double[] getConfidenceInterval​(double alpha, ConfidenceInterval side)
    returns the confidence interval based of the mean.
    String getDescription()
    returns the description of this tally.
    double getMax()
    Returns the max.
    double getMin()
    Returns the min.
    long getN()
    Returns the number of observations.
    double getPopulationExcessKurtosis()
    Return the population excess kurtosis of the ingested data.
    double getPopulationKurtosis()
    Return the (biased) population kurtosis of the ingested data.
    double getPopulationSkewness()
    Return the (biased) population skewness of the ingested data.
    double getPopulationStDev()
    Returns the current (biased) population standard deviation of all observations since the initialization.
    double getPopulationVariance()
    Returns the current (biased) population variance of all observations since the initialization.
    double getQuantile​(double probability)
    Compute the quantile for the given probability.
    double getSampleExcessKurtosis()
    Return the sample excess kurtosis of the ingested data.
    double getSampleKurtosis()
    Return the sample kurtosis of the ingested data.
    double getSampleMean()
    Returns the sample mean of all observations since the initialization.
    double getSampleSkewness()
    Return the (unbiased) sample skewness of the ingested data.
    double getSampleStDev()
    Returns the current (unbiased) sample standard deviation of all observations since the initialization.
    double getSampleVariance()
    Returns the current (unbiased) sample variance of all observations since the initialization.
    Serializable getSourceId()
    double getSum()
    Return the sum of the values of the observations.
    double ingest​(double value)
    Process one observed value.
    void initialize()
    initializes the Tally.
    void notify​(org.djutils.event.EventInterface event)
    String toString()

    Methods inherited from class org.djutils.event.EventProducer

    addListener, addListener, addListener, addListener, fireEvent, fireEvent, fireEvent, fireEvent, fireEvent, fireEvent, fireEvent, fireEvent, fireEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, getEventTypesWithListeners, getListenerReferences, hasListeners, numberOfListeners, removeAllListeners, removeAllListeners, removeListener

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

    Methods inherited from interface org.djutils.stats.summarizers.TallyInterface

    getPopulationMean

  • Constructor Details

    • EventBasedTally

      public EventBasedTally​(String description, QuantileAccumulator quantileAccumulator)
      Constructs a new EventBasedTally.
      Parameters:
      description - String; the description of this tally
      quantileAccumulator - QuantileAccumulator; the input series accumulator that can approximate or compute quantiles.

    • EventBasedTally

      public EventBasedTally​(String description)
      Convenience constructor that uses a NoStorageAccumulator to estimate quantiles.
      Parameters:
      description - String; the description of this tally

  • Method Details

    • getSourceId

      public Serializable getSourceId()
      Specified by:
      getSourceId in interface org.djutils.event.EventProducerInterface
      Specified by:
      getSourceId in class org.djutils.event.EventProducer

    • getSampleMean

      public final double getSampleMean()
      Returns the sample mean of all observations since the initialization.
      Specified by:
      getSampleMean in interface TallyInterface
      Returns:
      double; the sample mean

    • getQuantile

      public final double getQuantile​(double probability)
      Compute the quantile for the given probability.
      Specified by:
      getQuantile in interface TallyInterface
      Parameters:
      probability - double; the probability for which the quantile is to be computed. The value should be between 0 and 1, inclusive.
      Returns:
      double; the quantile for the probability

    • getConfidenceInterval

      public final double[] getConfidenceInterval​(double alpha)
      returns the confidence interval on either side of the mean.
      Specified by:
      getConfidenceInterval in interface TallyInterface
      Parameters:
      alpha - double; Alpha is the significance level used to compute the confidence level. The confidence level equals 100*(1 - alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level.
      Returns:
      double[]; the confidence interval of this tally

    • getConfidenceInterval

      public final double[] getConfidenceInterval​(double alpha, ConfidenceInterval side)
      returns the confidence interval based of the mean.
      Specified by:
      getConfidenceInterval in interface TallyInterface
      Parameters:
      alpha - double; Alpha is the significance level used to compute the confidence level. The confidence level equals 100*(1 - alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level.
      side - short; the side of the confidence interval with respect to the mean
      Returns:
      double[]; the confidence interval of this tally

    • getDescription

      public final String getDescription()
      returns the description of this tally.
      Specified by:
      getDescription in interface BasicTallyInterface
      Returns:
      Sting description

    • getMax

      public final double getMax()
      Returns the max.
      Specified by:
      getMax in interface BasicTallyInterface
      Returns:
      double

    • getMin

      public final double getMin()
      Returns the min.
      Specified by:
      getMin in interface BasicTallyInterface
      Returns:
      double

    • getN

      public final long getN()
      Returns the number of observations.
      Specified by:
      getN in interface BasicTallyInterface
      Returns:
      long n

    • getSampleStDev

      public final double getSampleStDev()
      Returns the current (unbiased) sample standard deviation of all observations since the initialization. The sample standard deviation is defined as the square root of the sample variance.
      Specified by:
      getSampleStDev in interface TallyInterface
      Returns:
      double; the sample standard deviation

    • getPopulationStDev

      public final double getPopulationStDev()
      Returns the current (biased) population standard deviation of all observations since the initialization. The population standard deviation is defined as the square root of the population variance.
      Specified by:
      getPopulationStDev in interface TallyInterface
      Returns:
      double; the population standard deviation

    • getSum

      public final double getSum()
      Return the sum of the values of the observations.
      Specified by:
      getSum in interface TallyInterface
      Returns:
      double; sum

    • getSampleVariance

      public final double getSampleVariance()
      Returns the current (unbiased) sample variance of all observations since the initialization. The calculation of the sample variance in relation to the population variance is undisputed. The formula is:
        S2 = (1 / (n - 1)) * [ Σx2 - (Σx)2 / n ]
      which can be calculated on the basis of the calculated population variance σ2 as follows:
        S2 = σ2 * n / (n - 1)
      Specified by:
      getSampleVariance in interface TallyInterface
      Returns:
      double; the current sample variance of this tally

    • getPopulationVariance

      public final double getPopulationVariance()
      Returns the current (biased) population variance of all observations since the initialization. The population variance is defined as:
      σ2 = (1 / n) * [ Σx2 - (Σx)2 / n ]
      Specified by:
      getPopulationVariance in interface TallyInterface
      Returns:
      double; the current population variance of this tally

    • getSampleSkewness

      public final double getSampleSkewness()
      Return the (unbiased) sample skewness of the ingested data. There are different formulas to calculate the unbiased (sample) skewness from the biased (population) skewness. Minitab, for instance calculates unbiased skewness as:
        Skewunbiased = Skewbiased [ ( n - 1) / n ] 3/2
      whereas SAS, SPSS and Excel calculate it as:
        Skewunbiased = Skewbiased √[ n ( n - 1)] / (n - 2)
      Here we follow the last mentioned formula. All formulas converge to the same value with larger n.
      Specified by:
      getSampleSkewness in interface TallyInterface
      Returns:
      double; the sample skewness of the ingested data

    • getPopulationSkewness

      public final double getPopulationSkewness()
      Return the (biased) population skewness of the ingested data. The population skewness is defined as:
        Skewbiased = [ Σ ( x - μ ) 3 ] / [ n . S3 ]
      where S2 is the sample variance. So the denominator is equal to [ n . sample_var3/2 ] .
      Specified by:
      getPopulationSkewness in interface TallyInterface
      Returns:
      double; the skewness of the ingested data

    • getSampleKurtosis

      public final double getSampleKurtosis()
      Return the sample kurtosis of the ingested data. The sample kurtosis can be defined in multiple ways. Here, we choose the following formula:
        Kurtunbiased = [ Σ ( x - μ ) 4 ] / [ ( n - 1 ) . S4 ]
      where S2 is the sample variance. So the denominator is equal to [ ( n - 1 ) . sample_var2 ] .
      Specified by:
      getSampleKurtosis in interface TallyInterface
      Returns:
      double; the sample kurtosis of the ingested data

    • getPopulationKurtosis

      public final double getPopulationKurtosis()
      Return the (biased) population kurtosis of the ingested data. The population kurtosis is defined as:
        Kurtbiased = [ Σ ( x - μ ) 4 ] / [ n . σ4 ]
      where σ2 is the population variance. So the denominator is equal to [ n . pop_var2 ] .
      Specified by:
      getPopulationKurtosis in interface TallyInterface
      Returns:
      double; the population kurtosis of the ingested data

    • getSampleExcessKurtosis

      public final double getSampleExcessKurtosis()
      Return the sample excess kurtosis of the ingested data. The sample excess kurtosis is the sample-corrected value of the excess kurtosis. Several formulas exist to calculate the sample excess kurtosis from the population kurtosis. Here we use:
        ExcessKurtunbiased = ( n - 1 ) / [( n - 2 ) * ( n - 3 )] [ ( n + 1 ) * ExcessKurtbiased + 6]
      This is the excess kurtosis that is calculated by, for instance, SAS, SPSS and Excel.
      Specified by:
      getSampleExcessKurtosis in interface TallyInterface
      Returns:
      double; the sample excess kurtosis of the ingested data

    • getPopulationExcessKurtosis

      public final double getPopulationExcessKurtosis()
      Return the population excess kurtosis of the ingested data. The kurtosis value of the normal distribution is 3. The excess kurtosis is the kurtosis value shifted by -3 to be 0 for the normal distribution.
      Specified by:
      getPopulationExcessKurtosis in interface TallyInterface
      Returns:
      double; the population excess kurtosis of the ingested data

    • initialize

      public void initialize()
      initializes the Tally. This methods sets the max, min, n, sum and variance values to their initial values.
      Specified by:
      initialize in interface BasicTallyInterface

    • notify

      public void notify​(org.djutils.event.EventInterface event)
      Specified by:
      notify in interface org.djutils.event.EventListenerInterface

    • ingest

      public double ingest​(double value)
      Process one observed value.
      Specified by:
      ingest in interface TallyInterface
      Parameters:
      value - double; the value to process
      Returns:
      double; the value

    • fireEvents

      protected void fireEvents()
      Method that can be overridden to fire own events or additional events when ingesting an observation.

    • toString

      public String toString()
      Overrides:
      toString in class Object