org.apache.commons.math3.stat.correlation
Class StorelessCovariance

java.lang.Object
  extended by org.apache.commons.math3.stat.correlation.Covariance
      extended by org.apache.commons.math3.stat.correlation.StorelessCovariance

public class StorelessCovariance
extends Covariance

Covariance implementation that does not require input data to be stored in memory. The size of the covariance matrix is specified in the constructor. Specific elements of the matrix are incrementally updated with calls to incrementRow() or increment Covariance().

This class is based on a paper written by Philippe Pébay: Formulas for Robust, One-Pass Parallel Computation of Covariances and Arbitrary-Order Statistical Moments, 2008, Technical Report SAND2008-6212, Sandia National Laboratories.

Note: the underlying covariance matrix is symmetric, thus only the upper triangular part of the matrix is stored and updated each increment.

Since:
3.0
Version:
$Id: StorelessCovariance.java 1410238 2012-11-16 07:58:49Z luc $

Constructor Summary
StorelessCovariance(int dim)
          Create a bias corrected covariance matrix with a given dimension.
StorelessCovariance(int dim, boolean biasCorrected)
          Create a covariance matrix with a given number of rows and columns and the indicated bias correction.
 
Method Summary
 double getCovariance(int xIndex, int yIndex)
          Get the covariance for an individual element of the covariance matrix.
 RealMatrix getCovarianceMatrix()
          Returns the covariance matrix
 double[][] getData()
          Return the covariance matrix as two-dimensional array.
 int getN()
          This Covariance method is not supported by a StorelessCovariance, since the number of bivariate observations does not have to be the same for different pairs of covariates - i.e., N as defined in Covariance.getN() is undefined.
 void increment(double[] data)
          Increment the covariance matrix with one row of data.
 
Methods inherited from class org.apache.commons.math3.stat.correlation.Covariance
computeCovarianceMatrix, computeCovarianceMatrix, computeCovarianceMatrix, computeCovarianceMatrix, covariance, covariance
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

StorelessCovariance

public StorelessCovariance(int dim)
Create a bias corrected covariance matrix with a given dimension.

Parameters:
dim - the dimension of the square covariance matrix

StorelessCovariance

public StorelessCovariance(int dim,
                           boolean biasCorrected)
Create a covariance matrix with a given number of rows and columns and the indicated bias correction.

Parameters:
dim - the dimension of the covariance matrix
biasCorrected - if true the covariance estimate is corrected for bias, i.e. n-1 in the denominator, otherwise there is no bias correction, i.e. n in the denominator.
Method Detail

getCovariance

public double getCovariance(int xIndex,
                            int yIndex)
                     throws NumberIsTooSmallException
Get the covariance for an individual element of the covariance matrix.

Parameters:
xIndex - row index in the covariance matrix
yIndex - column index in the covariance matrix
Returns:
the covariance of the given element
Throws:
NumberIsTooSmallException - if the number of observations in the cell is < 2

increment

public void increment(double[] data)
               throws DimensionMismatchException
Increment the covariance matrix with one row of data.

Parameters:
data - array representing one row of data.
Throws:
DimensionMismatchException - if the length of rowData does not match with the covariance matrix

getCovarianceMatrix

public RealMatrix getCovarianceMatrix()
                               throws NumberIsTooSmallException
Returns the covariance matrix

Overrides:
getCovarianceMatrix in class Covariance
Returns:
covariance matrix
Throws:
NumberIsTooSmallException - if the number of observations in a cell is < 2

getData

public double[][] getData()
                   throws NumberIsTooSmallException
Return the covariance matrix as two-dimensional array.

Returns:
a two-dimensional double array of covariance values
Throws:
NumberIsTooSmallException - if the number of observations for a cell is < 2

getN

public int getN()
         throws MathUnsupportedOperationException
This Covariance method is not supported by a StorelessCovariance, since the number of bivariate observations does not have to be the same for different pairs of covariates - i.e., N as defined in Covariance.getN() is undefined.

Overrides:
getN in class Covariance
Returns:
nothing as this implementation always throws a MathUnsupportedOperationException
Throws:
MathUnsupportedOperationException - in all cases


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