Package elki.math.statistics.dependence

Interface Dependence

All Known Implementing Classes:

DCor, HiCSDependence, HoeffdingsD, HoughSpaceMeasure, JensenShannonEquiwidthDependence, MaximumConditionalEntropy, MCDEDependence, MutualInformationEquiwidthDependence, PearsonCorrelationDependence, SlopeDependence, SlopeInversionDependence, SpearmanCorrelationDependence, SURFINGDependence

public interface Dependence

Measure the dependence of two variables.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Interface	Description
static class	Dependence.Utils	Utility functions that were previously in the abstract class.

Method Summary

Modifier and Type	Method	Description
default double	dependence(double[] data1, double[] data2)	Measure the dependence of two variables.
default <A> double	dependence(NumberArrayAdapter<?,A> adapter, A data1, A data2)	Measure the dependence of two variables.
<A,B> double	dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)	Measure the dependence of two variables.
default <A> double[]	dependence(NumberArrayAdapter<?,A> adapter, java.util.List<? extends A> data)	Measure the dependence of two variables.

Method Detail

dependence

<A,B> double dependence(NumberArrayAdapter<?,A> adapter1,
                              A data1,
                              NumberArrayAdapter<?,B> adapter2,
                              B data2)

Measure the dependence of two variables.

This is the more flexible API, which allows using different internal data representations.

Type Parameters:

A - First array type

B - Second array type

Parameters:

adapter1 - First data adapter

data1 - First data set

adapter2 - Second data adapter

data2 - Second data set

Returns:

Dependence measure

dependence

default <A> double dependence(NumberArrayAdapter<?,A> adapter,
                              A data1,
                              A data2)

Measure the dependence of two variables.

This is the more flexible API, which allows using different internal data representations.

Type Parameters:

A - Array type

Parameters:

adapter - Array type adapter

data1 - First data set

data2 - Second data set

Returns:

Dependence measure

dependence

default <A> double[] dependence(NumberArrayAdapter<?,A> adapter,
                                java.util.List<? extends A> data)

Measure the dependence of two variables.

This is the more flexible API, which allows using different internal data representations.

The resulting data is a serialized lower triangular matrix:

  X  S  S  S  S  S
  0  X  S  S  S  S
  1  2  X  S  S  S
  3  4  5  X  S  S
  6  7  8  9  X  S
 10 11 12 13 14  X
 

Type Parameters:

A - Array type

Parameters:

adapter - Data adapter

data - Data sets. Must have fast random access!

Returns:

Lower triangular serialized matrix

dependence

default double dependence(double[] data1,
                          double[] data2)

Measure the dependence of two variables.

Parameters:

data1 - First data set

data2 - Second data set

Returns:

Dependence measure