de.lmu.ifi.dbs.elki.math.statistics.tests

Class KolmogorovSmirnovTest

java.lang.Object

de.lmu.ifi.dbs.elki.math.statistics.tests.KolmogorovSmirnovTest

All Implemented Interfaces:

GoodnessOfFitTest

public class KolmogorovSmirnovTest
extends Object
implements GoodnessOfFitTest

Kolmogorov-Smirnov test. Class that tests two given real-valued data samples on whether they might have originated from the same underlying distribution using the Kolmogorov-Smirnov test statistic that compares the two empirical cumulative distribution functions. The KS statistic is defined as the maximum absolute difference of the empirical CDFs.

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	KolmogorovSmirnovTest.Parameterizer Parameterizer, to use the static instance.

Field Summary

Fields

Modifier and Type	Field and Description
static KolmogorovSmirnovTest	STATIC Static instance

Constructor Summary

Constructors

Constructor and Description
KolmogorovSmirnovTest() Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
static double	calculateTestStatistic(double[] sample1, double[] sample2) Calculates the maximum distance between the two empirical CDFs of two data samples.
double	deviation(double[] fullSample, double[] conditionalSample) Measure the deviation of a full sample from a conditional sample.
static double	simpleTest(double[] test) Simplest version of the test: test if a sorted array is approximately uniform distributed on [0:1].
static double	simpleTest(double[] test, double min, double max) Simplest version of the test: test if a sorted array is approximately uniform distributed on the given interval.

Methods inherited from class java.lang.Object

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

Field Detail

STATIC

public static KolmogorovSmirnovTest STATIC

Static instance

Constructor Detail

KolmogorovSmirnovTest

public KolmogorovSmirnovTest()

Constructor.

Method Detail

deviation

public double deviation(double[] fullSample,
               double[] conditionalSample)

Description copied from interface: GoodnessOfFitTest

Measure the deviation of a full sample from a conditional sample. Sample arrays may be modified, e.g. sorted, by the test.

Specified by:

deviation in interface GoodnessOfFitTest

Parameters:

fullSample - Full sample

conditionalSample - Conditional sample

Returns:

Deviation

calculateTestStatistic

public static double calculateTestStatistic(double[] sample1,
                            double[] sample2)

Calculates the maximum distance between the two empirical CDFs of two data samples. The sample positions and CDFs must be synchronized!

Parameters:

sample1 - first data sample positions

sample2 - second data sample positions

Returns:

the largest difference between both functions

simpleTest

public static double simpleTest(double[] test)

Simplest version of the test: test if a sorted array is approximately uniform distributed on [0:1].

Parameters:

test - Presorted (!) array

Returns:

Maximum deviation from uniform.

simpleTest

public static double simpleTest(double[] test,
                double min,
                double max)

Simplest version of the test: test if a sorted array is approximately uniform distributed on the given interval.

Parameters:

test - Presorted (!) array

min - Minimum of uniform distribution

max - Maximum of uniform distribution

Returns:

Maximum deviation from uniform.