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java.lang.Objectorg.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
public abstract class AbstractMultipleLinearRegression
Abstract base class for implementations of MultipleLinearRegression.
| Field Summary | |
|---|---|
protected RealMatrix |
X
X sample data. |
protected RealVector |
Y
Y sample data. |
| Constructor Summary | |
|---|---|
AbstractMultipleLinearRegression()
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| Method Summary | |
|---|---|
protected abstract RealVector |
calculateBeta()
Calculates the beta of multiple linear regression in matrix notation. |
protected abstract RealMatrix |
calculateBetaVariance()
Calculates the beta variance of multiple linear regression in matrix notation. |
protected RealVector |
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[] |
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. |
void |
newSampleData(double[] data,
int nobs,
int nvars)
Loads model x and y sample data from a flat array of data, overriding any previous sample. |
protected void |
newXSampleData(double[][] x)
Loads new x sample data, overriding any previous sample |
protected void |
newYSampleData(double[] y)
Loads new y sample data, overriding any previous sample |
protected void |
validateCovarianceData(double[][] x,
double[][] covariance)
Validates sample data. |
protected void |
validateSampleData(double[][] x,
double[] y)
Validates sample data. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
protected RealMatrix X
protected RealVector Y
| Constructor Detail |
|---|
public AbstractMultipleLinearRegression()
| Method Detail |
|---|
public void newSampleData(double[] data,
int nobs,
int nvars)
data - input data arraynobs - number of observations (rows)nvars - number of independent variables (columns, not counting y)protected void newYSampleData(double[] y)
y - the [n,1] array representing the y sampleprotected void newXSampleData(double[][] x)
x - the [n,k] array representing the x sample
protected void validateSampleData(double[][] x,
double[] y)
x - the [n,k] array representing the x sampley - the [n,1] array representing the y sample
IllegalArgumentException - if the x and y array data are not
compatible for the regression
protected void validateCovarianceData(double[][] x,
double[][] covariance)
x - the [n,k] array representing the x samplecovariance - the [n,n] array representing the covariance matrix
IllegalArgumentException - if the x sample data or covariance
matrix are not compatible for the regressionpublic double[] estimateRegressionParameters()
estimateRegressionParameters in interface MultipleLinearRegressionpublic double[] estimateResiduals()
estimateResiduals in interface MultipleLinearRegressionpublic double[][] estimateRegressionParametersVariance()
estimateRegressionParametersVariance in interface MultipleLinearRegressionpublic double[] estimateRegressionParametersStandardErrors()
estimateRegressionParametersStandardErrors in interface MultipleLinearRegressionpublic double estimateRegressandVariance()
estimateRegressandVariance in interface MultipleLinearRegressionprotected abstract RealVector calculateBeta()
protected abstract RealMatrix calculateBetaVariance()
protected abstract double calculateYVariance()
protected RealVector calculateResiduals()
u = y - X * b
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