org.apache.commons.math3.stat.correlation

## Class Covariance

• Direct Known Subclasses:
StorelessCovariance

public class Covariance
extends Object
Computes covariances for pairs of arrays or columns of a matrix.

The constructors that take RealMatrix or double[][] arguments generate covariance matrices. The columns of the input matrices are assumed to represent variable values.

The constructor argument biasCorrected determines whether or not computed covariances are bias-corrected.

Unbiased covariances are given by the formula

cov(X, Y) = Σ[(xi - E(X))(yi - E(Y))] / (n - 1) where E(X) is the mean of X and E(Y) is the mean of the Y values.

Non-bias-corrected estimates use n in place of n - 1

Since:
2.0
• ### Constructor Summary

Constructors
Constructor and Description
Covariance()
Create a Covariance with no data
Covariance(double[][] data)
Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(double[][] data, boolean biasCorrected)
Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(RealMatrix matrix)
Create a covariance matrix from a matrix whose columns represent covariates.
Covariance(RealMatrix matrix, boolean biasCorrected)
Create a covariance matrix from a matrix whose columns represent covariates.
• ### Constructor Detail

• #### Covariance

public Covariance()
Create a Covariance with no data
• #### Covariance

public Covariance(double[][] data,
boolean biasCorrected)
throws MathIllegalArgumentException,
NotStrictlyPositiveException
Create a Covariance matrix from a rectangular array whose columns represent covariates.

The biasCorrected parameter determines whether or not covariance estimates are bias-corrected.

The input array must be rectangular with at least one column and two rows.

Parameters:
data - rectangular array with columns representing covariates
biasCorrected - true means covariances are bias-corrected
Throws:
MathIllegalArgumentException - if the input data array is not rectangular with at least two rows and one column.
NotStrictlyPositiveException - if the input data array is not rectangular with at least one row and one column.
• #### Covariance

public Covariance(RealMatrix matrix,
boolean biasCorrected)
throws MathIllegalArgumentException
Create a covariance matrix from a matrix whose columns represent covariates.

The biasCorrected parameter determines whether or not covariance estimates are bias-corrected.

The matrix must have at least one column and two rows

Parameters:
matrix - matrix with columns representing covariates
biasCorrected - true means covariances are bias-corrected
Throws:
MathIllegalArgumentException - if the input matrix does not have at least two rows and one column
• #### Covariance

public Covariance(RealMatrix matrix)
throws MathIllegalArgumentException
Create a covariance matrix from a matrix whose columns represent covariates.

The matrix must have at least one column and two rows

Parameters:
matrix - matrix with columns representing covariates
Throws:
MathIllegalArgumentException - if the input matrix does not have at least two rows and one column