drasys.or.stat.model
Class LinearCorrelation

java.lang.Object
  |
  +--drasys.or.stat.model.LinearCorrelation

public class LinearCorrelation

extends java.lang.Object

Computes the correlation and covariance matrices for multiple random variables.

References:

Mathematical Statistics : Basic Ideas and Selected Topics
    Peter J. Bickel / Hardcover / Published 1991
Introduction to Mathematical Statistics
    Robert V. Hogg, Allen T. Craig (Contributor) / Hardcover / Published 1995
Mathematical Statistics With Applications
    Dennis D. Wackerly, et al / Hardcover / Published 1996
Probability and Statistics
    Morris H. Degroot / Hardcover / Published 1986
Numerical Recipes in C : The Art of Scientific Computing
    William H. Press, et al / Hardcover / Published 1993

Constructor Summary

LinearCorrelation(MatrixI samples)           Initialize the correlation with the samples.

 

Method Summary
ContiguousMatrix	getCorrelation()           Returns the correlation coefficients for all the column pairs.
ContiguousMatrix	getCovariance()           Returns the covariances for all of the column pairs.
ContiguousMatrix	getLowerBound(double confidenceLevel)           Computes the lower bound of the confidence interval.
ContiguousVector	getMean()           Returns the sample arithmetic means for all of the columns.
ContiguousVector	getStd()           Returns the sample standard deviation for all of the columns.
ContiguousMatrix	getSumOfProducts()           Returns the sum of the products for all of the column pairs.
ContiguousVector	getSumOfSquares()           Returns the sum of the squares for all of the columns.
ContiguousMatrix	getUpperBound(double confidenceLevel)           Computes the upper bound of the confidence interval.

 

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

 

Constructor Detail

LinearCorrelation

public LinearCorrelation(MatrixI samples)

Initialize the correlation with the samples. Each column contains one random variable and the rows contain the samples.

getMean

public ContiguousVector getMean()

Returns the sample arithmetic means for all of the columns.

getStd

public ContiguousVector getStd()

Returns the sample standard deviation for all of the columns.

getSumOfSquares

public ContiguousVector getSumOfSquares()

Returns the sum of the squares for all of the columns.

getSumOfProducts

public ContiguousMatrix getSumOfProducts()

Returns the sum of the products for all of the column pairs.

getCovariance

public ContiguousMatrix getCovariance()

Returns the covariances for all of the column pairs.

getCorrelation

public ContiguousMatrix getCorrelation()

Returns the correlation coefficients for all the column pairs.

getLowerBound

public ContiguousMatrix getLowerBound(double confidenceLevel)

Computes the lower bound of the confidence interval.

getUpperBound

public ContiguousMatrix getUpperBound(double confidenceLevel)

Computes the upper bound of the confidence interval.