org.apache.commons.math3.stat.descriptive.moment

## Class VectorialCovariance

- java.lang.Object
- - org.apache.commons.math3.stat.descriptive.moment.VectorialCovariance

All Implemented Interfaces:
  Serializable

    public class VectorialCovariance
    extends Object
    implements Serializable

Returns the covariance matrix of the available vectors.

Since:
  1.2
Version:
  $Id: VectorialCovariance.java 1416643 2012-12-03 19:37:14Z tn $
See Also:
  Serialized Form

### Field Summary

Fields
`private boolean` `isBiasCorrected` Indicator for bias correction.
`private long` `n` Number of vectors in the sample.
`private double[]` `productsSums` Sums of products for each component.
`private static long` `serialVersionUID` Serializable version identifier
`private double[]` `sums` Sums for each component.

### Constructor Summary

Constructors
Constructor and Description
`VectorialCovariance(int dimension, boolean isBiasCorrected)` Constructs a VectorialCovariance.

### Method Summary

Methods
`void` `clear()` Clears the internal state of the Statistic
`boolean` `equals(Object obj)`
`long` `getN()` Get the number of vectors in the sample.
`RealMatrix` `getResult()` Get the covariance matrix.
`int` `hashCode()`
`void` `increment(double[] v)` Add a new vector to the sample.

### Methods inherited from class java.lang.Object

`clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait`

### Field Detail

#### serialVersionUID

    private static final long serialVersionUID

Serializable version identifier

See Also:
  Constant Field Values

#### sums

    private final double[] sums

Sums for each component.

#### productsSums

    private final double[] productsSums

Sums of products for each component.

#### isBiasCorrected

    private final boolean isBiasCorrected

Indicator for bias correction.

#### n

    private long n

Number of vectors in the sample.

### Constructor Detail

#### VectorialCovariance

    public VectorialCovariance(int dimension,
                       boolean isBiasCorrected)

Constructs a VectorialCovariance.

Parameters:
  `dimension` - vectors dimension
  `isBiasCorrected` - if true, computed the unbiased sample covariance, otherwise computes the biased population covariance

### Method Detail

#### increment

    public void increment(double[] v)
                   throws DimensionMismatchException

Add a new vector to the sample.

Parameters:
  `v` - vector to add
Throws:
  `DimensionMismatchException` - if the vector does not have the right dimension

#### getResult

    public RealMatrix getResult()

Get the covariance matrix.

Returns:
  covariance matrix

#### getN

    public long getN()

Get the number of vectors in the sample.

Returns:
  number of vectors in the sample

#### clear

    public void clear()

Clears the internal state of the Statistic

#### hashCode

    public int hashCode()

Overrides:
  `hashCode` in class `Object`

#### equals

    public boolean equals(Object obj)

Overrides:
  `equals` in class `Object`