GLSMultipleLinearRegressionTest (Commons Math 3.2 Test API)

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org.apache.commons.math3.stat.regression
Class GLSMultipleLinearRegressionTest

java.lang.Object
  org.apache.commons.math3.stat.regression.MultipleLinearRegressionAbstractTest
      org.apache.commons.math3.stat.regression.GLSMultipleLinearRegressionTest

public class GLSMultipleLinearRegressionTest
extends MultipleLinearRegressionAbstractTest
extends MultipleLinearRegressionAbstractTest

Field Summary

Fields inherited from class org.apache.commons.math3.stat.regression.MultipleLinearRegressionAbstractTest
`regression`

Constructor Summary
`GLSMultipleLinearRegressionTest()`

Method Summary
`void`	`cannotAddCovarianceDataThatIsNotSquare()`
`void`	`cannotAddCovarianceDataWithSampleSizeMismatch()`
`void`	`cannotAddNullCovarianceData()`
`void`	`cannotAddNullYSampleData()`
`void`	`cannotAddSampleDataWithSizeMismatch()`
`void`	`cannotAddXSampleData()`
`protected GLSMultipleLinearRegression`	`createRegression()`
`protected int`	`getNumberOfRegressors()`
`protected int`	`getSampleSize()`
`void`	`notEnoughData()`
`void`	`setUp()`
`void`	`testGLSEfficiency()` Generate an error covariance matrix and sample data representing models with this error structure.
`void`	`testGLSOLSConsistency()` Verifies that GLS with identity covariance matrix gives the same results as OLS.
`void`	`testNewSample2()` Verifies that setting X, Y and covariance separately has the same effect as newSample(X,Y,cov).
`void`	`testYVariance()` test calculateYVariance

Methods inherited from class org.apache.commons.math3.stat.regression.MultipleLinearRegressionAbstractTest
`canEstimateRegressandVariance, canEstimateRegressionParameters, canEstimateRegressionParametersVariance, canEstimateResiduals, testNewSample, testNewSampleInsufficientData, testNewSampleInvalidData, testNewSampleNullData, testXSampleDataNull, testYSampleDataNull`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

GLSMultipleLinearRegressionTest

public GLSMultipleLinearRegressionTest()

Method Detail

setUp

public void setUp()

Overrides:: setUp in class MultipleLinearRegressionAbstractTest

cannotAddXSampleData

public void cannotAddXSampleData()

cannotAddNullYSampleData

public void cannotAddNullYSampleData()

cannotAddSampleDataWithSizeMismatch

public void cannotAddSampleDataWithSizeMismatch()

cannotAddNullCovarianceData

public void cannotAddNullCovarianceData()

notEnoughData

public void notEnoughData()

cannotAddCovarianceDataWithSampleSizeMismatch

public void cannotAddCovarianceDataWithSampleSizeMismatch()

cannotAddCovarianceDataThatIsNotSquare

public void cannotAddCovarianceDataThatIsNotSquare()

createRegression

protected GLSMultipleLinearRegression createRegression()

Specified by:: createRegression in class MultipleLinearRegressionAbstractTest

getNumberOfRegressors

protected int getNumberOfRegressors()

Specified by:: getNumberOfRegressors in class MultipleLinearRegressionAbstractTest

getSampleSize

protected int getSampleSize()

Specified by:: getSampleSize in class MultipleLinearRegressionAbstractTest

testYVariance

public void testYVariance()

test calculateYVariance

testNewSample2

public void testNewSample2()

Verifies that setting X, Y and covariance separately has the same effect as newSample(X,Y,cov).

testGLSOLSConsistency

public void testGLSOLSConsistency()

Verifies that GLS with identity covariance matrix gives the same results as OLS.

testGLSEfficiency

public void testGLSEfficiency()

Generate an error covariance matrix and sample data representing models with this error structure. Then verify that GLS estimated coefficients, on average, perform better than OLS.