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new b3a8489de MATH-1392: Respect no-intercept models in sample size
validation (#337)
b3a8489de is described below
commit b3a8489de7a5127dcda900ee9cb6d9975c065ef2
Author: hutiefang76 <[email protected]>
AuthorDate: Sat Oct 24 07:15:55 2026 -0700
MATH-1392: Respect no-intercept models in sample size validation (#337)
Permit square full-rank OLS and GLS designs without an intercept while
preserving default-intercept and underdetermined-input validation.
Document that error variance remains unavailable at zero residual DOF.
Generated-by: DeepSeek
Generated-by: Codex
---
.../AbstractMultipleLinearRegression.java | 30 +++++++----
.../GLSMultipleLinearRegressionTest.java | 44 ++++++++++++++++
.../OLSMultipleLinearRegressionTest.java | 60 ++++++++++++++++++++++
src/changes/changes.xml | 6 +++
4 files changed, 130 insertions(+), 10 deletions(-)
diff --git
a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/regression/AbstractMultipleLinearRegression.java
b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/regression/AbstractMultipleLinearRegression.java
index 727551e10..b6d832cef 100644
---
a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/regression/AbstractMultipleLinearRegression.java
+++
b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/regression/AbstractMultipleLinearRegression.java
@@ -99,7 +99,11 @@ public abstract class AbstractMultipleLinearRegression
implements
* <p>Throws IllegalArgumentException if any of the following
preconditions fail:
* <ul><li><code>data</code> cannot be null</li>
* <li><code>data.length = nobs * (nvars + 1)</code></li>
- * <li>{@code nobs > nvars}</li></ul>
+ * <li>{@code nobs > 0} and either {@code nobs >= nvars} when {@code
noIntercept} is
+ * set, or {@code nobs > nvars} otherwise</li></ul>
+ * <p>Note that when the number of observations equals the number of
design columns
+ * ({@code nobs == nvars} with {@code noIntercept} set) the error variance
cannot be
+ * estimated.</p>
*
* @param data input data array
* @param nobs number of observations (rows)
@@ -107,8 +111,9 @@ public abstract class AbstractMultipleLinearRegression
implements
* @throws NullArgumentException if the data array is null
* @throws DimensionMismatchException if the length of the data array is
not equal
* to <code>nobs * (nvars + 1)</code>
- * @throws InsufficientDataException if <code>nobs</code> is less than
- * <code>nvars + 1</code>
+ * @throws InsufficientDataException if <code>nobs</code> is not positive,
or if it is
+ * less than <code>nvars</code> when {@code noIntercept} is set, or if it
is not
+ * larger than <code>nvars</code> otherwise
*/
public void newSampleData(double[] data, int nobs, int nvars) {
if (data == null) {
@@ -117,8 +122,9 @@ public abstract class AbstractMultipleLinearRegression
implements
if (data.length != nobs * (nvars + 1)) {
throw new DimensionMismatchException(data.length, nobs * (nvars +
1));
}
- if (nobs <= nvars) {
- throw new
InsufficientDataException(LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE,
nobs, nvars + 1);
+ if (noIntercept ? (nobs < nvars || nobs == 0) : nobs <= nvars) {
+ throw new
InsufficientDataException(LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE,
nobs,
+ noIntercept ? nvars : nvars + 1);
}
double[] y = new double[nobs];
final int cols = noIntercept ? nvars: nvars + 1;
@@ -205,10 +211,12 @@ public abstract class AbstractMultipleLinearRegression
implements
* Validates sample data. Checks that
* <ul><li>Neither x nor y is null or empty;</li>
* <li>The length (i.e. number of rows) of x equals the length of y</li>
- * <li>x has at least one more row than it has columns (i.e. there is
- * sufficient data to estimate regression coefficients for each of the
- * columns in x plus an intercept.</li>
+ * <li>x has at least as many rows as required design columns, i.e. the
+ * number of columns in x plus an intercept column when {@code noIntercept}
+ * is not set.</li>
* </ul>
+ * <p>Note that when the number of observations equals the number of design
+ * columns the error variance cannot be estimated.</p>
*
* @param x the [n,k] array representing the x data
* @param y the [n,1] array representing the y data
@@ -217,7 +225,8 @@ public abstract class AbstractMultipleLinearRegression
implements
* have the same length
* @throws NoDataException if {@code x} or {@code y} are zero-length
* @throws MathIllegalArgumentException if the number of rows of {@code x}
- * is not larger than the number of columns + 1
+ * is less than the number of design columns (an equal number of rows is
+ * accepted)
*/
protected void validateSampleData(double[][] x, double[] y) throws
MathIllegalArgumentException {
if (x == null || y == null) {
@@ -229,7 +238,8 @@ public abstract class AbstractMultipleLinearRegression
implements
if (x.length == 0) { // Must be no y data either
throw new NoDataException();
}
- if (x[0].length + 1 > x.length) {
+ final int requiredColumns = x[0].length + (noIntercept ? 0 : 1);
+ if (requiredColumns > x.length) {
throw new MathIllegalArgumentException(
LocalizedFormats.NOT_ENOUGH_DATA_FOR_NUMBER_OF_PREDICTORS,
x.length, x[0].length);
diff --git
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/GLSMultipleLinearRegressionTest.java
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/GLSMultipleLinearRegressionTest.java
index 7878c002f..66e4a46df 100644
---
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/GLSMultipleLinearRegressionTest.java
+++
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/GLSMultipleLinearRegressionTest.java
@@ -27,11 +27,13 @@ import org.apache.commons.rng.simple.RandomSource;
import org.apache.commons.statistics.distribution.ContinuousDistribution;
import org.apache.commons.statistics.distribution.NormalDistribution;
import org.apache.commons.math4.legacy.TestUtils;
+import org.apache.commons.math4.legacy.exception.DimensionMismatchException;
import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
import org.apache.commons.math4.legacy.exception.NullArgumentException;
import org.apache.commons.math4.legacy.linear.MatrixUtils;
import org.apache.commons.math4.legacy.linear.RealMatrix;
import org.apache.commons.math4.legacy.linear.RealVector;
+import org.apache.commons.math4.legacy.linear.SingularMatrixException;
import org.apache.commons.math4.legacy.random.CorrelatedVectorFactory;
import org.apache.commons.math4.legacy.stat.correlation.Covariance;
import org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics;
@@ -91,6 +93,48 @@ public class GLSMultipleLinearRegressionTest extends
MultipleLinearRegressionAbs
createRegression().newSampleData(null, new double[][]{}, null);
}
+ @Test
+ public void testGlsNoInterceptMatrixExactFit() {
+ final GLSMultipleLinearRegression regression = new
GLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[][] x = {{1d, 2d}, {3d, 4d}};
+ final double[] y = {5d, 11d};
+ final double[][] covariance = {{2d, 0d}, {0d, 4d}};
+ regression.newSampleData(y, x, covariance);
+ final double[] params = regression.estimateRegressionParameters();
+ Assert.assertArrayEquals(new double[] {1d, 2d}, params, 1e-10);
+ }
+
+ @Test(expected=MathIllegalArgumentException.class)
+ public void testGlsNoInterceptUnderdeterminedSampleDataRejected() {
+ final GLSMultipleLinearRegression regression = new
GLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[][] x = {{1d, 2d, 3d}, {4d, 5d, 6d}};
+ final double[] y = {5d, 11d};
+ final double[][] covariance = {{2d, 0d}, {0d, 4d}};
+ regression.newSampleData(y, x, covariance);
+ }
+
+ @Test(expected=DimensionMismatchException.class)
+ public void testGlsCovarianceRowCountMismatchRejected() {
+ final GLSMultipleLinearRegression regression = new
GLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[][] x = {{1d, 2d}, {3d, 4d}, {5d, 7d}};
+ final double[] y = {5d, 11d, 17d};
+ final double[][] covariance = {{2d, 0d}, {0d, 4d}};
+ regression.newSampleData(y, x, covariance);
+ }
+
+ @Test(expected=SingularMatrixException.class)
+ public void testGlsSingularCovarianceEstimateRejected() {
+ final GLSMultipleLinearRegression regression = new
GLSMultipleLinearRegression();
+ final double[][] x = {{1d}, {2d}, {3d}};
+ final double[] y = {5d, 11d, 17d};
+ final double[][] covariance = {{1d, 1d, 0d}, {1d, 1d, 0d}, {0d, 0d,
1d}};
+ regression.newSampleData(y, x, covariance);
+ regression.estimateRegressionParameters();
+ }
+
@Test(expected=MathIllegalArgumentException.class)
public void cannotAddSampleDataWithSizeMismatch() {
double[] y = new double[]{1.0, 2.0};
diff --git
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/OLSMultipleLinearRegressionTest.java
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/OLSMultipleLinearRegressionTest.java
index 3444c8e1e..a44b296d3 100644
---
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/OLSMultipleLinearRegressionTest.java
+++
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/regression/OLSMultipleLinearRegressionTest.java
@@ -66,6 +66,66 @@ public class OLSMultipleLinearRegressionTest extends
MultipleLinearRegressionAbs
return y.length;
}
+ @Test(expected =
org.apache.commons.math4.legacy.exception.InsufficientDataException.class)
+ public void testNewSampleDataFlatWithInterceptInsufficientObservations() {
+ // nobs = 2 and nvars = 2 need 3 design columns with the default
intercept.
+ final double[] data = { 1, 2, 3, 4, 5, 6 };
+ new OLSMultipleLinearRegression().newSampleData(data, 2, 2);
+ }
+
+ @Test(expected =
org.apache.commons.math4.legacy.exception.InsufficientDataException.class)
+ public void testNewSampleDataFlatNoInterceptEmptyData() {
+ final OLSMultipleLinearRegression regression = new
OLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ regression.newSampleData(new double[0], 0, 0);
+ }
+
+ @Test
+ public void testOlsNoInterceptMatrixExactFit() {
+ final OLSMultipleLinearRegression regression = new
OLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[][] x = {{1d, 2d}, {3d, 4d}};
+ final double[] y = {5d, 11d};
+ regression.newSampleData(y, x);
+ final double[] params = regression.estimateRegressionParameters();
+ Assert.assertArrayEquals(new double[] {1d, 2d}, params, 1e-12);
+ }
+
+ @Test
+ public void testOlsNoInterceptFlatExactFit() {
+ final OLSMultipleLinearRegression regression = new
OLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[] data = {5d, 1d, 2d, 11d, 3d, 4d};
+ regression.newSampleData(data, 2, 2);
+ final double[] params = regression.estimateRegressionParameters();
+ Assert.assertArrayEquals(new double[] {1d, 2d}, params, 1e-12);
+ }
+
+ @Test(expected=MathIllegalArgumentException.class)
+ public void testOlsNoInterceptMatrixUnderdeterminedSampleDataRejected() {
+ final OLSMultipleLinearRegression regression = new
OLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[][] x = {{1d, 2d, 3d}, {4d, 5d, 6d}};
+ final double[] y = {5d, 11d};
+ regression.newSampleData(y, x);
+ }
+
+ @Test(expected=MathIllegalArgumentException.class)
+ public void testOlsNoInterceptFlatUnderdeterminedSampleDataRejected() {
+ final OLSMultipleLinearRegression regression = new
OLSMultipleLinearRegression();
+ regression.setNoIntercept(true);
+ final double[] data = {5d, 1d, 2d, 3d, 11d, 4d, 5d, 6d};
+ regression.newSampleData(data, 2, 3);
+ }
+
+ @Test(expected=MathIllegalArgumentException.class)
+ public void testOlsDefaultInterceptSquareSampleDataRejected() {
+ final OLSMultipleLinearRegression regression = new
OLSMultipleLinearRegression();
+ final double[][] x = {{1d, 2d}, {3d, 4d}};
+ final double[] y = {5d, 11d};
+ regression.newSampleData(y, x);
+ }
+
@Test(expected=MathIllegalArgumentException.class)
public void cannotAddSampleDataWithSizeMismatch() {
double[] y = new double[]{1.0, 2.0};
diff --git a/src/changes/changes.xml b/src/changes/changes.xml
index b111a20cc..1fd4bb183 100644
--- a/src/changes/changes.xml
+++ b/src/changes/changes.xml
@@ -104,6 +104,12 @@ Caveat:
<action type="fix" issue="MATH-1678">
"CanberraDistance": Avoid overflow for large finite coordinates.
</action>
+ <action type="fix" issue="MATH-1392">
+ Sample size validation in multiple linear regression now counts the
+ design columns that are actually used, so that a model without an
+ intercept is no longer rejected when the number of observations
+ equals the number of independent variables.
+ </action>
<action dev="aherbert" type="fix" due-to="Lyin-OTTF">
"SynchronizedDescriptiveStatistics": Synchronize all mutators
of the internal state. Updates previously unsynchronized methods
