org.hipparchus.stat.correlation

Class SpearmansCorrelation

java.lang.Object

org.hipparchus.stat.correlation.SpearmansCorrelation

public class SpearmansCorrelation
extends Object

Spearman's rank correlation. This implementation performs a rank transformation on the input data and then computes PearsonsCorrelation on the ranked data.

By default, ranks are computed using NaturalRanking with default strategies for handling NaNs and ties in the data (NaNs maximal, ties averaged). The ranking algorithm can be set using a constructor argument.

Constructor Summary

Constructors

Constructor and Description
SpearmansCorrelation() Create a SpearmansCorrelation without data.
SpearmansCorrelation(RankingAlgorithm rankingAlgorithm) Create a SpearmansCorrelation with the given ranking algorithm.
SpearmansCorrelation(RealMatrix dataMatrix) Create a SpearmansCorrelation from the given data matrix.
SpearmansCorrelation(RealMatrix dataMatrix, RankingAlgorithm rankingAlgorithm) Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.

Method Summary

Modifier and Type	Method and Description
RealMatrix	computeCorrelationMatrix(double[][] matrix) Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.
RealMatrix	computeCorrelationMatrix(RealMatrix matrix) Computes the Spearman's rank correlation matrix for the columns of the input matrix.
double	correlation(double[] xArray, double[] yArray) Computes the Spearman's rank correlation coefficient between the two arrays.
RealMatrix	getCorrelationMatrix() Calculate the Spearman Rank Correlation Matrix.
PearsonsCorrelation	getRankCorrelation() Returns a PearsonsCorrelation instance constructed from the ranked input data.

Methods inherited from class java.lang.Object

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

Constructor Detail

SpearmansCorrelation

public SpearmansCorrelation()

Create a SpearmansCorrelation without data.

SpearmansCorrelation

public SpearmansCorrelation(RankingAlgorithm rankingAlgorithm)
                     throws MathIllegalArgumentException

Create a SpearmansCorrelation with the given ranking algorithm.

Parameters:

rankingAlgorithm - ranking algorithm

Throws:

MathIllegalArgumentException - if the provided RankingAlgorithm is of type NaturalRanking and uses a NaNStrategy.REMOVED strategy

SpearmansCorrelation

public SpearmansCorrelation(RealMatrix dataMatrix)

Create a SpearmansCorrelation from the given data matrix.

Parameters:

dataMatrix - matrix of data with columns representing variables to correlate

SpearmansCorrelation

public SpearmansCorrelation(RealMatrix dataMatrix,
                            RankingAlgorithm rankingAlgorithm)
                     throws MathIllegalArgumentException

Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.

Parameters:

dataMatrix - matrix of data with columns representing variables to correlate

rankingAlgorithm - ranking algorithm

Throws:

MathIllegalArgumentException - if the provided RankingAlgorithm is of type NaturalRanking and uses a NaNStrategy.REMOVED strategy

Method Detail

getCorrelationMatrix

public RealMatrix getCorrelationMatrix()

Calculate the Spearman Rank Correlation Matrix.

Returns:

Spearman Rank Correlation Matrix

Throws:

NullPointerException - if this instance was created with no data

getRankCorrelation

public PearsonsCorrelation getRankCorrelation()

Returns a PearsonsCorrelation instance constructed from the ranked input data. That is, new SpearmansCorrelation(matrix).getRankCorrelation() is equivalent to new PearsonsCorrelation(rankTransform(matrix)) where rankTransform(matrix) is the result of applying the configured RankingAlgorithm to each of the columns of matrix.

Returns null if this instance was created with no data.

Returns:

PearsonsCorrelation among ranked column data

computeCorrelationMatrix

public RealMatrix computeCorrelationMatrix(RealMatrix matrix)

Computes the Spearman's rank correlation matrix for the columns of the input matrix.

Parameters:

matrix - matrix with columns representing variables to correlate

Returns:

correlation matrix

computeCorrelationMatrix

public RealMatrix computeCorrelationMatrix(double[][] matrix)

Computes the Spearman's rank correlation matrix for the columns of the input rectangular array. The columns of the array represent values of variables to be correlated.

Parameters:

matrix - matrix with columns representing variables to correlate

Returns:

correlation matrix

correlation

public double correlation(double[] xArray,
                          double[] yArray)

Computes the Spearman's rank correlation coefficient between the two arrays.

Parameters:

xArray - first data array

yArray - second data array

Returns:

Returns Spearman's rank correlation coefficient for the two arrays

Throws:

MathIllegalArgumentException - if the arrays lengths do not match

MathIllegalArgumentException - if the array length is less than 2