dev.nm.stat.descriptive.correlation

Class SpearmanRankCorrelation

java.lang.Object

dev.nm.stat.descriptive.correlation.SpearmanRankCorrelation

All Implemented Interfaces:

Statistic

public class SpearmanRankCorrelation
extends Object
implements Statistic

Spearman's rank correlation coefficient or Spearman's rho is a non-parametric measure of statistical dependence between two variables. It assesses how well the relationship between two variables can be described using a monotonic function. If there are no repeated data values, a perfect Spearman correlation of +1 or -1 occurs when each of the variables is a perfect monotone function of the other.

For a set of observations \((X_i, Y_i)\) we first compute the ranks \(x_i\) and \(y_i\) of the \(X\) and \(Y\) values for each observation. Spearman's rho is defined as the Pearson correlation coefficient between the ranked variables: \[ \rho = \frac{\sum_i(x_i-\bar{x})(y_i-\bar{y})}{\sqrt{\sum_i (x_i-\bar{x})^2 \sum_i(y_i-\bar{y})^2}} \]

See Also:

Wikipedia: Spearman's rank correlation coefficient, Covariance.correlation()

Constructor Summary

Constructors

Constructor and Description
SpearmanRankCorrelation(double[] data1, double[] data2) Construct a Spearman rank calculator initialized with two samples.

Method Summary

Modifier and Type	Method and Description
void	addData(double... data) Update the statistic with more data.
void	addData(double[] data1, double[] data2) Add the given two samples.
long	N() Get the size of the sample.
double	value() Get the value of the statistic.

Methods inherited from class java.lang.Object

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

Constructor Detail

SpearmanRankCorrelation

public SpearmanRankCorrelation(double[] data1,
                               double[] data2)

Construct a Spearman rank calculator initialized with two samples. The size of the two sample must be equal.

Parameters:

data1 - the first sample

data2 - the second sample

Method Detail

addData

public void addData(double... data)

Update the statistic with more data. Since this signature takes only a single array double[], we concatenate the two arrays into one.

For example, suppose we want to do

 
 addData(new double[][]{
     {1, 2, 3},
     {4, 5, 6}
 });
 
 

We can also write

 
 addData(new double[]{
     {1, 2, 3, 4, 5, 6}
 });
 
 

In the latter case, there must be an even number of data points.

Specified by:

addData in interface Statistic

Parameters:

data - a data array concatenating two samples

addData

public void addData(double[] data1,
                    double[] data2)

Add the given two samples. The size of the two samples must be equal.

Parameters:

data1 - the first sample

data2 - the second sample

N

public long N()

Description copied from interface: Statistic

Get the size of the sample.

Specified by:

N in interface Statistic

Returns:

the sample size

value

public double value()

Description copied from interface: Statistic

Get the value of the statistic.

Specified by:

value in interface Statistic

Returns:

the statistic