Package org.apache.commons.math.stat.correlation

Class SpearmansCorrelation

java.lang.Object

org.apache.commons.math.stat.correlation.SpearmansCorrelation

public class SpearmansCorrelation
extends java.lang.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.

Since:

2.0

Constructor Summary

Constructors

Constructor	Description
SpearmansCorrelation()	Create a SpearmansCorrelation without data.
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	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

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

Constructor Detail

SpearmansCorrelation

public SpearmansCorrelation(RealMatrix dataMatrix,
                            RankingAlgorithm rankingAlgorithm)

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

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()

Create a SpearmansCorrelation without data.

Method Detail

getCorrelationMatrix

public RealMatrix getCorrelationMatrix()

Calculate the Spearman Rank Correlation Matrix.

Returns:

Spearman Rank Correlation Matrix

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:

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)
                   throws java.lang.IllegalArgumentException

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

Throws IllegalArgumentException if the arrays do not have the same length or their common length is less than 2

Parameters:

xArray - first data array

yArray - second data array

Returns:

Returns Spearman's rank correlation coefficient for the two arrays

Throws:

java.lang.IllegalArgumentException - if the arrays lengths do not match or there is insufficient data