Covariance (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.stat.correlation.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[(x_i - E(X))(y_i - 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.

Method Summary

Methods
Modifier and Type	Method and Description
`protected RealMatrix`	`computeCovarianceMatrix(double[][] data)` Create a covariance matrix from a rectangular array whose columns represent covariates.
`protected RealMatrix`	`computeCovarianceMatrix(double[][] data, boolean biasCorrected)` Compute a covariance matrix from a rectangular array whose columns represent covariates.
`protected RealMatrix`	`computeCovarianceMatrix(RealMatrix matrix)` Create a covariance matrix from a matrix whose columns represent covariates.
`protected RealMatrix`	`computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected)` Compute a covariance matrix from a matrix whose columns represent covariates.
`double`	`covariance(double[] xArray, double[] yArray)` Computes the covariance between the two arrays, using the bias-corrected formula.
`double`	`covariance(double[] xArray, double[] yArray, boolean biasCorrected)` Computes the covariance between the two arrays.
`RealMatrix`	`getCovarianceMatrix()` Returns the covariance matrix
`int`	`getN()` Returns the number of observations (length of covariate vectors)

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- 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(double[][] data)
           throws MathIllegalArgumentException,
                  NotStrictlyPositiveException
```
    Create a Covariance matrix from a rectangular array whose columns represent covariates.
    The input array must be rectangular with at least one column and two rows
    
    Parameters:
    data - rectangular array with columns representing covariates
    
    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
- Method Detail
  - getCovarianceMatrix
```
public RealMatrix getCovarianceMatrix()
```
    Returns the covariance matrix
    
    Returns:
    covariance matrix
  - getN
```
public int getN()
```
    Returns the number of observations (length of covariate vectors)
    
    Returns:
    number of observations
  - computeCovarianceMatrix
```
protected RealMatrix computeCovarianceMatrix(RealMatrix matrix,
                                 boolean biasCorrected)
                                      throws MathIllegalArgumentException
```
    Compute a covariance matrix from a matrix whose columns represent covariates.
    
    Parameters:
    matrix - input matrix (must have at least one column and two rows)
    biasCorrected - determines whether or not covariance estimates are bias-corrected
    
    Returns:
    covariance matrix
    
    Throws:
    
    MathIllegalArgumentException - if the matrix does not contain sufficient data
  - computeCovarianceMatrix
```
protected RealMatrix computeCovarianceMatrix(RealMatrix matrix)
                                      throws MathIllegalArgumentException
```
    Create a covariance matrix from a matrix whose columns represent covariates. Covariances are computed using the bias-corrected formula.
    
    Parameters:
    matrix - input matrix (must have at least one column and two rows)
    
    Returns:
    covariance matrix
    
    Throws:
    
    MathIllegalArgumentException - if matrix does not contain sufficient data
    See Also:
    Covariance(org.apache.commons.math3.linear.RealMatrix)
  - computeCovarianceMatrix
```
protected RealMatrix computeCovarianceMatrix(double[][] data,
                                 boolean biasCorrected)
                                      throws MathIllegalArgumentException,
                                             NotStrictlyPositiveException
```
    Compute a covariance matrix from a rectangular array whose columns represent covariates.
    
    Parameters:
    data - input array (must have at least one column and two rows)
    biasCorrected - determines whether or not covariance estimates are bias-corrected
    
    Returns:
    covariance matrix
    
    Throws:
    
    MathIllegalArgumentException - if the data array does not contain sufficient data
    
    NotStrictlyPositiveException - if the input data array is not rectangular with at least one row and one column.
  - computeCovarianceMatrix
```
protected RealMatrix computeCovarianceMatrix(double[][] data)
                                      throws MathIllegalArgumentException,
                                             NotStrictlyPositiveException
```
    Create a covariance matrix from a rectangular array whose columns represent covariates. Covariances are computed using the bias-corrected formula.
    
    Parameters:
    data - input array (must have at least one column and two rows)
    
    Returns:
    covariance matrix
    
    Throws:
    
    MathIllegalArgumentException - if the data array does not contain sufficient data
    
    NotStrictlyPositiveException - if the input data array is not rectangular with at least one row and one column.
    See Also:
    Covariance(org.apache.commons.math3.linear.RealMatrix)
  - covariance
```
public double covariance(double[] xArray,
                double[] yArray,
                boolean biasCorrected)
                  throws MathIllegalArgumentException
```
    Computes the covariance between the two arrays.
    Array lengths must match and the common length must be at least 2.
    
    Parameters:
    xArray - first data array
    yArray - second data array
    biasCorrected - if true, returned value will be bias-corrected
    
    Returns:
    returns the covariance for the two arrays
    
    Throws:
    
    MathIllegalArgumentException - if the arrays lengths do not match or there is insufficient data
  - covariance
```
public double covariance(double[] xArray,
                double[] yArray)
                  throws MathIllegalArgumentException
```
    Computes the covariance between the two arrays, using the bias-corrected formula.
    Array lengths must match and the common length must be at least 2.
    
    Parameters:
    xArray - first data array
    yArray - second data array
    
    Returns:
    returns the covariance for the two arrays
    
    Throws:
    
    MathIllegalArgumentException - if the arrays lengths do not match or there is insufficient data

Class Covariance

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Covariance

Covariance

Covariance

Covariance

Covariance

Method Detail

getCovarianceMatrix

getN

computeCovarianceMatrix

computeCovarianceMatrix

computeCovarianceMatrix

computeCovarianceMatrix

covariance

covariance