## org.apache.commons.math.stat.descriptive.moment
Class VectorialCovariance

    java.lang.Object
      org.apache.commons.math.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:
  $Revision: 922714 $ $Date: 2010-03-14 02:35:14 +0100 (dim. 14 mars 2010) $
See Also:
  Serialized Form

Field Summary
`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
`VectorialCovariance(int dimension, boolean isBiasCorrected)` Constructs a VectorialCovariance.

Method Summary
`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`

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