gov.sandia.cognition.statistics.distribution

Class KolmogorovDistribution

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.AbstractDistribution<NumberType>

gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<java.lang.Double>

gov.sandia.cognition.statistics.distribution.KolmogorovDistribution

All Implemented Interfaces:

Vectorizable, ClosedFormDistribution<java.lang.Double>, ClosedFormUnivariateDistribution<java.lang.Double>, Distribution<java.lang.Double>, DistributionWithMean<java.lang.Double>, UnivariateDistribution<java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

KolmogorovDistribution.CDF

@PublicationReference(author="Wikipedia",
                      title="Kolmogorov-Smirnov test, Kolmogorov distribution",
                      type=WebPage,
                      year=2009,
                      url="http://en.wikipedia.org/wiki/Kolmogorov_distribution#Kolmogorov_distribution")
public class KolmogorovDistribution
extends AbstractClosedFormUnivariateDistribution<java.lang.Double>

Contains the Cumulative Distribution Function description for the "D" statistic used within the Kolmogorov-Smirnov test.

Since:

2.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	KolmogorovDistribution.CDF Contains the Cumulative Distribution Function description for the "D" statistic used within the Kolmogorov-Smirnov test.

Field Summary

Fields

Modifier and Type	Field and Description
static double	MEAN Value of the mean, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.868481392844716.
static double	VARIANCE Value of the variance, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.06759934611527044.

Constructor Summary

Constructors

Constructor and Description
KolmogorovDistribution() Creates a new instance of CumulativeDistribution

Method Summary

Modifier and Type	Method and Description
void	convertFromVector(Vector parameters) Converts the object from a Vector of parameters.
Vector	convertToVector() Converts the object to a vector.
KolmogorovDistribution.CDF	getCDF() Gets the CDF of a scalar distribution.
java.lang.Double	getMaxSupport() Gets the minimum support (domain or input) of the distribution.
java.lang.Double	getMean() Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.
double	getMeanAsDouble() Gets the mean of the distribution as a double.
java.lang.Double	getMinSupport() Gets the minimum support (domain or input) of the distribution.
double	getVariance() Gets the variance of the distribution.
void	sampleInto(java.util.Random random, int sampleCount, java.util.Collection<? super java.lang.Double> output) Draws multiple random samples from the distribution and puts the result into the given collection.

Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution

clone

Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

sample, sample

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.statistics.Distribution

sample, sample

Field Detail

MEAN

public static final double MEAN

Value of the mean, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.868481392844716.

See Also:

Constant Field Values

VARIANCE

public static final double VARIANCE

Value of the variance, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.06759934611527044.

See Also:

Constant Field Values

Constructor Detail

KolmogorovDistribution

public KolmogorovDistribution()

Creates a new instance of CumulativeDistribution

Method Detail

getMean

public java.lang.Double getMean()

Description copied from interface: DistributionWithMean

Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.

Returns:

Mean of the distribution.

getMeanAsDouble

public double getMeanAsDouble()

Description copied from interface: UnivariateDistribution

Gets the mean of the distribution as a double.

Returns:

The mean as a double.

sampleInto

public void sampleInto(java.util.Random random,
                       int sampleCount,
                       java.util.Collection<? super java.lang.Double> output)

Description copied from interface: Distribution

Draws multiple random samples from the distribution and puts the result into the given collection.

Parameters:

random - Random number generator to use.

sampleCount - The number of samples to draw. Cannot be negative.

output - The collection to add the samples into.

getVariance

public double getVariance()

Description copied from interface: UnivariateDistribution

Gets the variance of the distribution. This is sometimes called the second central moment by more pedantic people, which is equivalent to the square of the standard deviation.

Returns:

Variance of the distribution.

getCDF

public KolmogorovDistribution.CDF getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Returns:

CDF of the scalar distribution.

convertToVector

public Vector convertToVector()

Description copied from interface: Vectorizable

Converts the object to a vector.

Returns:

The Vector form of the object.

convertFromVector

public void convertFromVector(Vector parameters)

Description copied from interface: Vectorizable

Converts the object from a Vector of parameters.

Parameters:

parameters - The parameters to incorporate.

getMinSupport

public java.lang.Double getMinSupport()

Description copied from interface: UnivariateDistribution

Gets the minimum support (domain or input) of the distribution.

Returns:

Minimum support.

getMaxSupport

public java.lang.Double getMaxSupport()

Description copied from interface: UnivariateDistribution

Gets the minimum support (domain or input) of the distribution.

Returns:

Minimum support.