MultipleLinearRegression (Commons Math 3.2 API)

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org.apache.commons.math3.stat.regression
Interface MultipleLinearRegression

All Known Implementing Classes:: AbstractMultipleLinearRegression, GLSMultipleLinearRegression, OLSMultipleLinearRegression

public interface MultipleLinearRegression

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

  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.

Since:: 2.0
Version:: $Id: MultipleLinearRegression.java 1416643 2012-12-03 19:37:14Z tn $

Method Summary
`double`	`estimateRegressandVariance()` Returns the variance of the regressand, ie Var(y).
`double[]`	`estimateRegressionParameters()` Estimates the regression parameters b.
`double[]`	`estimateRegressionParametersStandardErrors()` Returns the standard errors of the regression parameters.
`double[][]`	`estimateRegressionParametersVariance()` Estimates the variance of the regression parameters, ie Var(b).
`double[]`	`estimateResiduals()` Estimates the residuals, ie u = y - X*b.

Method Detail

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

estimateRegressionParametersStandardErrors

double[] estimateRegressionParametersStandardErrors()

Returns the standard errors of the regression parameters.

Returns:: standard errors of estimated regression parameters