org.codehaus.jet.regression
Interface MultipleLinearRegressionEstimator

All Known Implementing Classes:
AbstractMultipleLinearRegressionEstimator, GLSMultipleLinearRegressionEstimator, OLSMultipleLinearRegressionEstimator

public interface MultipleLinearRegressionEstimator

The multiple linear regression can be represented in matrix-notation as

  y=X*b+u
 
where y is an n-vector regressand, X is a [n,k] matrix whose k columns are called regressors, b is k-vector of regression parameters and u is an n-vector of error terms or residuals. The notation is quite standard in literature, cf eg Davidson and MacKinnon, Econometrics Theory and Methods, 2004.

Author:
Mauro Talevi

Method Summary
 void addData(double[] y, double[][] x, double[][] covariance)
          Adds sample and covariance data
 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
 

Method Detail

addData

void addData(double[] y,
             double[][] x,
             double[][] covariance)
Adds sample and covariance data

Parameters:
y - the [n,1] array representing the y sample
x - the [n,k] array representing x sample
covariance - the [n,n] array representing the covariance matrix or null if not appropriate for the specific implementation

estimateRegressionParameters

double[] estimateRegressionParameters()
Estimates the regression parameters b

Returns:
The [k,1] array representing b

estimateRegressionParametersVariance

double[][] estimateRegressionParametersVariance()
Estimates the variance of the regression parameters, ie Var(b)

Returns:
The [k,k] array representing the variance of b

estimateResiduals

double[] estimateResiduals()
Estimates the residuals, ie u = y - X*b

Returns:
The [n,1] array representing the residuals

estimateRegressandVariance

double estimateRegressandVariance()
Returns the variance of the regressand, ie Var(y)

Returns:
The double representing the variance of y


Copyright © 2006-2007. All Rights Reserved.