org.openjump.core.attributeoperations.statistics

Class CorrelationCoefficients

java.lang.Object

org.openjump.core.attributeoperations.statistics.CorrelationCoefficients

public class CorrelationCoefficients
extends java.lang.Object

Class that calculates various correlation coefficients.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	CorrelationCoefficients.CorrelationInformation
class	CorrelationCoefficients.RankCorrelationInformation
protected class	CorrelationCoefficients.SpearmanRankNumberPair

Field Summary

Fields

Modifier and Type	Field and Description
protected java.lang.String	attrName1
protected java.lang.String	attrName2
protected java.lang.Object[]	dataArray
protected double[]	means
protected Feature[]	rawFeatures

Constructor Summary

Constructors

Constructor and Description
CorrelationCoefficients(Feature[] features, java.lang.String attr1, java.lang.String attr2)

Method Summary

Methods

Modifier and Type	Method and Description
protected double	aritmeticMiddle(Feature[] features, int attr)
static double	getDeviation(Feature[] features, java.lang.String attr, double mean) Returns the deviation of the values of the given attribute.
CorrelationCoefficients.RankCorrelationInformation	getKendalsTauRankCoefficient() "Spearman Rank Order Correlations (or "rho") and Kendall's Tau-b (or "tau") Correlations are used when the variables are measured as ranks (from highest-to-lowest or lowest-to-highest)" http://www.themeasurementgroup.com/datamining/definitions/correlation.htm
double	getMean(int nr) Get the aritmetic middle for the nr-th attribut given
CorrelationCoefficients.CorrelationInformation	getPearsonCoefficient() get Pearson's correlation coefficient (good, dimension-less measure, if there is a linear relation between the attributes) see: http://www.netzwelt.de/lexikon/Korrelationskoeffizient.html
protected java.util.HashMap<java.lang.Integer,java.lang.Double>	getRank2SpearmanRankMap(java.lang.Object[] sortedValues, java.util.HashMap<java.lang.Object,java.lang.Integer> value2NumAppearances)
CorrelationCoefficients.RankCorrelationInformation	getSpearmansRhoCoefficient() get Pearson's correlation coefficient (good, dimension-less measure, if there is a linear relation between the attributes) see: http://www.netzwelt.de/lexikon/Korrelationskoeffizient.html
protected double	getVariance(java.lang.String attr)
protected CorrelationDataPair[]	initializeDataStorage(Feature[] features)

Methods inherited from class java.lang.Object

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

Field Detail

dataArray

protected java.lang.Object[] dataArray

attrName1

protected java.lang.String attrName1

attrName2

protected java.lang.String attrName2

means

protected double[] means

rawFeatures

protected Feature[] rawFeatures

Constructor Detail

CorrelationCoefficients

public CorrelationCoefficients(Feature[] features,
                       java.lang.String attr1,
                       java.lang.String attr2)

Method Detail

initializeDataStorage

protected CorrelationDataPair[] initializeDataStorage(Feature[] features)

getDeviation

public static double getDeviation(Feature[] features,
                  java.lang.String attr,
                  double mean)

Returns the deviation of the values of the given attribute. Uses a given mean to avoid multiple calculation of the mean. To get the mean take a look at the FeatureCollectionTools class. This class is also used by aritmeticMiddle().

Parameters:

features - array containing the features we want the deviation for

attr - name of the attribute to calculate the deviation for

mean - the mean for the given features

Returns:

the deviation

Throws:

java.lang.IllegalArgumentException - if the attribute is not of a numerical type

See Also:

FeatureCollectionTools

getVariance

protected double getVariance(java.lang.String attr)

aritmeticMiddle

protected double aritmeticMiddle(Feature[] features,
                     int attr)

getMean

public double getMean(int nr)

Get the aritmetic middle for the nr-th attribut given

Parameters:

nr - index number of attribut to calculate the mean for

Returns:

the mean for the attribute or Double.NaN, if errors occured

getPearsonCoefficient

public CorrelationCoefficients.CorrelationInformation getPearsonCoefficient()

get Pearson's correlation coefficient (good, dimension-less measure, if there is a linear relation between the attributes)
see: http://www.netzwelt.de/lexikon/Korrelationskoeffizient.html

Returns:

Pearson's correlation coefficient

getRank2SpearmanRankMap

protected java.util.HashMap<java.lang.Integer,java.lang.Double> getRank2SpearmanRankMap(java.lang.Object[] sortedValues,
                                                                            java.util.HashMap<java.lang.Object,java.lang.Integer> value2NumAppearances)

getSpearmansRhoCoefficient

public CorrelationCoefficients.RankCorrelationInformation getSpearmansRhoCoefficient()

get Pearson's correlation coefficient (good, dimension-less measure, if there is a linear relation between the attributes)
see: http://www.netzwelt.de/lexikon/Korrelationskoeffizient.html

Returns:

Pearson's correlation coefficient

getKendalsTauRankCoefficient

public CorrelationCoefficients.RankCorrelationInformation getKendalsTauRankCoefficient()

"Spearman Rank Order Correlations (or "rho") and Kendall's Tau-b (or "tau") Correlations are used when the variables are measured as ranks (from highest-to-lowest or lowest-to-highest)"
http://www.themeasurementgroup.com/datamining/definitions/correlation.htm

Returns:

RankCorrelationInformation