Apache
/
commons-math
mirror of https://github.com/apache/commons-math.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Improved or corrected javadoc; added some tests.

This commit is contained in:
Phil Steitz 2015-01-10 20:02:30 -07:00
parent e42ab0ec6c
commit 3a7519fcb1
2 changed files with 53 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

27
src/main/java/org/apache/commons/math3/stat/regression/OLSMultipleLinearRegression.java
View File

@ -156,12 +156,11 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
* the {@link #calculateRSquared() R-squared} computation.</p>
*
* @return SSTO - the total sum of squares
* @throws MathIllegalArgumentException if the sample has not been set or does
* not contain at least 3 observations
* @throws NullPointerException if the sample has not been set
* @see #isNoIntercept()
* @since 2.2
*/
public double calculateTotalSumOfSquares() throws MathIllegalArgumentException {
public double calculateTotalSumOfSquares() {
if (isNoIntercept()) {
return StatUtils.sumSq(getY().toArray());
} else {
@ -174,6 +173,8 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
*
* @return residual sum of squares
* @since 2.2
* @throws org.apache.commons.math3.linear.SingularMatrixException if the design matrix is singular
* @throws NullPointerException if the data for the model have not been loaded
*/
public double calculateResidualSumOfSquares() {
final RealVector residuals = calculateResiduals();
@ -188,12 +189,14 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
* where SSR is the {@link #calculateResidualSumOfSquares() sum of squared residuals}
* and SSTO is the {@link #calculateTotalSumOfSquares() total sum of squares}
*
* <p>If there is no variance in y, i.e., SSTO = 0, NaN is returned.</p>
*
* @return R-square statistic
* @throws MathIllegalArgumentException if the sample has not been set or does
* not contain at least 3 observations
* @throws NullPointerException if the sample has not been set
* @throws org.apache.commons.math3.linear.SingularMatrixException if the design matrix is singular
* @since 2.2
*/
public double calculateRSquared() throws MathIllegalArgumentException {
public double calculateRSquared() {
return 1 - calculateResidualSumOfSquares() / calculateTotalSumOfSquares();
}
@ -209,13 +212,15 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
* <code> 1 - (1 - {@link #calculateRSquared()}) * (n / (n - p)) </code>
* </pre></p>
*
* <p>If there is no variance in y, i.e., SSTO = 0, NaN is returned.</p>
*
* @return adjusted R-Squared statistic
* @throws MathIllegalArgumentException if the sample has not been set or does
* not contain at least 3 observations
* @throws NullPointerException if the sample has not been set
* @throws org.apache.commons.math3.linear.SingularMatrixException if the design matrix is singular
* @see #isNoIntercept()
* @since 2.2
*/
public double calculateAdjustedRSquared() throws MathIllegalArgumentException {
public double calculateAdjustedRSquared() {
final double n = getX().getRowDimension();
if (isNoIntercept()) {
return 1 - (1 - calculateRSquared()) * (n / (n - getX().getColumnDimension()));
@ -244,6 +249,8 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
* a {@code NullPointerException} will be thrown.</p>
*
* @return beta
* @throws org.apache.commons.math3.linear.SingularMatrixException if the design matrix is singular
* @throws NullPointerException if the data for the model have not been loaded
*/
@Override
protected RealVector calculateBeta() {
@ -264,6 +271,8 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
* a {@code NullPointerException} will be thrown.</p>
*
* @return The beta variance-covariance matrix
* @throws org.apache.commons.math3.linear.SingularMatrixException if the design matrix is singular
* @throws NullPointerException if the data for the model have not been loaded
*/
@Override
protected RealMatrix calculateBetaVariance() {

35
src/test/java/org/apache/commons/math3/stat/regression/OLSMultipleLinearRegressionTest.java
View File

@ -782,4 +782,39 @@ public class OLSMultipleLinearRegressionTest extends MultipleLinearRegressionAbs
TestUtils.assertEquals(835542680000.000, model.calculateResidualSumOfSquares(), 1.0e-3);
return;
}
/**
* Anything requiring beta calculation should advertise SME.
*/
@Test(expected=org.apache.commons.math3.linear.SingularMatrixException.class)
public void testSingularCalculateBeta() {
OLSMultipleLinearRegression model = new OLSMultipleLinearRegression();
model.newSampleData(new double[] {1, 2, 3, 1, 2, 3, 1, 2, 3}, 3, 2);
model.calculateBeta();
}
@Test
public void testNoSSTOCalculateRsquare() {
OLSMultipleLinearRegression model = new OLSMultipleLinearRegression();
model.newSampleData(new double[] {1, 2, 3, 1, 7, 8, 1, 10, 12}, 3, 2);
Assert.assertTrue(Double.isNaN(model.calculateRSquared()));
}
@Test(expected=NullPointerException.class)
public void testNoDataNPECalculateBeta() {
OLSMultipleLinearRegression model = new OLSMultipleLinearRegression();
model.calculateBeta();
}
@Test(expected=NullPointerException.class)
public void testNoDataNPECalculateHat() {
OLSMultipleLinearRegression model = new OLSMultipleLinearRegression();
model.calculateHat();
}
@Test(expected=NullPointerException.class)
public void testNoDataNPESSTO() {
OLSMultipleLinearRegression model = new OLSMultipleLinearRegression();
model.calculateTotalSumOfSquares();
}
}