java.lang.Object
- org.djutils.event.EventProducer
- - org.djutils.stats.summarizers.event.EventBasedTally

All Implemented Interfaces:

Serializable, EventListener, EventListenerInterface, EventProducerInterface, BasicTallyInterface, TallyInterface
```
public class EventBasedTally
extends EventProducer
implements 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) 2002-2021 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

All Methods Instance Methods Concrete Methods
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(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, fireEvent, fireEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireTimedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, fireUnverifiedTimedEvent, 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 Detail
  - 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 Detail
  - getSourceId
```
public Serializable getSourceId()
```
    Specified by:
    
    getSourceId in interface EventProducerInterface
    
    Specified by:
    
    getSourceId in class 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 - ConfidenceInterval; 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:
    Skew_unbiased = Skew_biased [ ( n - 1) / n ]^3/2
    whereas SAS, SPSS and Excel calculate it as:
    Skew_unbiased = Skew_biased √[ 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:
    Skew_biased = [ Σ ( x - μ ) ³ ] / [ n . S³ ]
    where S² is the sample variance. So the denominator is equal to [ n . sample_var^3/2 ] .
    
    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:
    Kurt_unbiased = [ 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:
    Kurt_biased = [ 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:
    ExcessKurt_unbiased = ( n - 1 ) / [( n - 2 ) * ( n - 3 )] [ ( n + 1 ) * ExcessKurt_biased + 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(EventInterface event)
```
    Specified by:
    
    notify in interface 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

Class EventBasedTally

Field Summary

Fields inherited from class org.djutils.event.EventProducer

Fields inherited from interface org.djutils.event.EventProducerInterface

Constructor Summary

Method Summary

Methods inherited from class org.djutils.event.EventProducer

Methods inherited from class java.lang.Object

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

Constructor Detail

EventBasedTally

EventBasedTally

Method Detail

getSourceId

getSampleMean

getQuantile

getConfidenceInterval

getConfidenceInterval

getDescription

getMax

getMin

getN

getSampleStDev

getPopulationStDev

getSum

getSampleVariance

getPopulationVariance

getSampleSkewness

getPopulationSkewness

getSampleKurtosis

getPopulationKurtosis

getSampleExcessKurtosis

getPopulationExcessKurtosis

initialize

notify

ingest

fireEvents

toString