Package org.apache.commons.math.stat.descriptive.moment

Class Kurtosis

java.lang.Object

org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic

org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic

org.apache.commons.math.stat.descriptive.moment.Kurtosis

All Implemented Interfaces:

java.io.Serializable, StorelessUnivariateStatistic, UnivariateStatistic

public class Kurtosis
extends AbstractStorelessUnivariateStatistic
implements java.io.Serializable

Computes the Kurtosis of the available values.

We use the following (unbiased) formula to define kurtosis:

kurtosis = { [n(n+1) / (n -1)(n - 2)(n-3)] sum[(x_i - mean)^4] / std^4 } - [3(n-1)^2 / (n-2)(n-3)]

where n is the number of values, mean is the Mean and std is the StandardDeviation

Note that this statistic is undefined for n < 4. Double.Nan is returned when there is not sufficient data to compute the statistic.

Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the increment() or clear() method, it must be synchronized externally.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor	Description
Kurtosis()	Construct a Kurtosis
Kurtosis(FourthMoment m4)	Construct a Kurtosis from an external moment
Kurtosis(Kurtosis original)	Copy constructor, creates a new Kurtosis identical to the original

Method Summary

Modifier and Type	Method	Description
void	clear()	Clears the internal state of the Statistic
Kurtosis	copy()	Returns a copy of the statistic with the same internal state.
static void	copy(Kurtosis source, Kurtosis dest)	Copies source to dest.
double	evaluate(double[] values, int begin, int length)	Returns the kurtosis of the entries in the specified portion of the input array.
long	getN()	Returns the number of values that have been added.
double	getResult()	Returns the current value of the Statistic.
void	increment(double d)	Updates the internal state of the statistic to reflect the addition of the new value.

Methods inherited from class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic

equals, evaluate, hashCode, incrementAll, incrementAll

Methods inherited from class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic

evaluate, getData, setData, setData

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Kurtosis

public Kurtosis()

Construct a Kurtosis

Kurtosis

public Kurtosis(FourthMoment m4)

Construct a Kurtosis from an external moment

Parameters:

m4 - external Moment

Kurtosis

public Kurtosis(Kurtosis original)

Copy constructor, creates a new Kurtosis identical to the original

Parameters:

original - the Kurtosis instance to copy

Method Detail

increment

public void increment(double d)

Updates the internal state of the statistic to reflect the addition of the new value.

Specified by:

increment in interface StorelessUnivariateStatistic

Specified by:

increment in class AbstractStorelessUnivariateStatistic

Parameters:

d - the new value.

getResult

public double getResult()

Returns the current value of the Statistic.

Specified by:

getResult in interface StorelessUnivariateStatistic

Specified by:

getResult in class AbstractStorelessUnivariateStatistic

Returns:

value of the statistic, Double.NaN if it has been cleared or just instantiated.

clear

public void clear()

Clears the internal state of the Statistic

Specified by:

clear in interface StorelessUnivariateStatistic

Specified by:

clear in class AbstractStorelessUnivariateStatistic

getN

public long getN()

Returns the number of values that have been added.

Specified by:

getN in interface StorelessUnivariateStatistic

Returns:

the number of values.

evaluate

public double evaluate(double[] values,
                       int begin,
                       int length)

Returns the kurtosis of the entries in the specified portion of the input array.

See Kurtosis for details on the computing algorithm.

Throws IllegalArgumentException if the array is null.

Specified by:

evaluate in interface UnivariateStatistic

Overrides:

evaluate in class AbstractStorelessUnivariateStatistic

Parameters:

values - the input array

begin - index of the first array element to include

length - the number of elements to include

Returns:

the kurtosis of the values or Double.NaN if length is less than 4

Throws:

java.lang.IllegalArgumentException - if the input array is null or the array index parameters are not valid

See Also:

UnivariateStatistic.evaluate(double[], int, int)

copy

public Kurtosis copy()

Returns a copy of the statistic with the same internal state.

Specified by:

copy in interface StorelessUnivariateStatistic

Specified by:

copy in interface UnivariateStatistic

Specified by:

copy in class AbstractStorelessUnivariateStatistic

Returns:

a copy of the statistic

copy

public static void copy(Kurtosis source,
                        Kurtosis dest)

Copies source to dest.

Neither source nor dest can be null.

Parameters:

source - Kurtosis to copy

dest - Kurtosis to copy to

Throws:

java.lang.NullPointerException - if either source or dest is null