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
See Also:
  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    private final boolean
    Indicator for bias correction.
    private long
    Number of vectors in the sample.
    private final double[]
    Sums of products for each component.
    private static final long
    Serializable version identifier
    private final double[]
    Sums for each component.
  • Constructor Summary

    Constructors
    Constructor
    Description
    VectorialCovariance(int dimension, boolean isBiasCorrected)
    Constructs a VectorialCovariance.
  • Method Summary

    Modifier and Type
    Method
    Description
    void
    Clears the internal state of the Statistic
    boolean
    long
    Get the number of vectors in the sample.
    Get the covariance matrix.
    int
    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 Details

    • serialVersionUID

      private static final long serialVersionUID
      Serializable version identifier
      See Also:
    • 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 Details

    • 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 Details

    • 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