org.codehaus.jet.regression.estimators
Class AbstractMultipleLinearRegressionEstimator

java.lang.Object
  extended by org.codehaus.jet.regression.estimators.AbstractMultipleLinearRegressionEstimator
All Implemented Interfaces:
MultipleLinearRegressionEstimator
Direct Known Subclasses:
GLSMultipleLinearRegressionEstimator, OLSMultipleLinearRegressionEstimator

public abstract class AbstractMultipleLinearRegressionEstimator
extends java.lang.Object
implements MultipleLinearRegressionEstimator

Abstract base class for implementations of MultipleLinearRegression

Author:
Mauro Talevi

Field Summary
protected  org.apache.commons.math.linear.RealMatrix X
           
protected  org.apache.commons.math.linear.RealMatrix Y
           
 
Constructor Summary
AbstractMultipleLinearRegressionEstimator()
           
 
Method Summary
protected  void addXSampleData(double[][] x)
          Adds x sample data
protected  void addYSampleData(double[] y)
          Adds y sample data
protected abstract  org.apache.commons.math.linear.RealMatrix calculateBeta()
          Calculates the beta of multiple linear regression in matrix notation
protected abstract  org.apache.commons.math.linear.RealMatrix calculateBetaVariance()
          Calculates the beta variance of multiple linear regression in matrix notation
protected  org.apache.commons.math.linear.RealMatrix calculateResiduals()
          Calculates the residuals of multiple linear regression in matrix notation
protected abstract  double calculateYVariance()
          Calculates the Y variance of multiple linear regression
 double estimateRegressandVariance()
          Returns the variance of the regressand, ie Var(y)
 double[] estimateRegressionParameters()
          Estimates the regression parameters b
 double[][] estimateRegressionParametersVariance()
          Estimates the variance of the regression parameters, ie Var(b)
 double[] estimateResiduals()
          Estimates the residuals, ie u = y - X*b
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface org.codehaus.jet.regression.MultipleLinearRegressionEstimator
addData
 

Field Detail

X

protected org.apache.commons.math.linear.RealMatrix X

Y

protected org.apache.commons.math.linear.RealMatrix Y
Constructor Detail

AbstractMultipleLinearRegressionEstimator

public AbstractMultipleLinearRegressionEstimator()
Method Detail

addYSampleData

protected void addYSampleData(double[] y)
Adds y sample data

Parameters:
y - the [n,1] array representing the y sample

addXSampleData

protected void addXSampleData(double[][] x)
Adds x sample data

Parameters:
x - the [n,k] array representing the x sample

estimateRegressionParameters

public double[] estimateRegressionParameters()
Description copied from interface: MultipleLinearRegressionEstimator
Estimates the regression parameters b

Specified by:
estimateRegressionParameters in interface MultipleLinearRegressionEstimator
Returns:
The [k,1] array representing b

estimateResiduals

public double[] estimateResiduals()
Description copied from interface: MultipleLinearRegressionEstimator
Estimates the residuals, ie u = y - X*b

Specified by:
estimateResiduals in interface MultipleLinearRegressionEstimator
Returns:
The [n,1] array representing the residuals

estimateRegressionParametersVariance

public double[][] estimateRegressionParametersVariance()
Description copied from interface: MultipleLinearRegressionEstimator
Estimates the variance of the regression parameters, ie Var(b)

Specified by:
estimateRegressionParametersVariance in interface MultipleLinearRegressionEstimator
Returns:
The [k,k] array representing the variance of b

estimateRegressandVariance

public double estimateRegressandVariance()
Description copied from interface: MultipleLinearRegressionEstimator
Returns the variance of the regressand, ie Var(y)

Specified by:
estimateRegressandVariance in interface MultipleLinearRegressionEstimator
Returns:
The double representing the variance of y

calculateBeta

protected abstract org.apache.commons.math.linear.RealMatrix calculateBeta()
Calculates the beta of multiple linear regression in matrix notation


calculateBetaVariance

protected abstract org.apache.commons.math.linear.RealMatrix calculateBetaVariance()
Calculates the beta variance of multiple linear regression in matrix notation


calculateYVariance

protected abstract double calculateYVariance()
Calculates the Y variance of multiple linear regression


calculateResiduals

protected org.apache.commons.math.linear.RealMatrix calculateResiduals()
Calculates the residuals of multiple linear regression in matrix notation
 u = y - X*b
 

Returns:
The residuals [n,1] matrix


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