Fixed error in computing discrete distribution of D statistics for small-sample
2-sample Kolmogorov-Smirnov tests. Error was causing incorrect p-values returned by exactP and monteCarloP methods (used by default for small, mid-size samples). JIRA: MATH-1245
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@ -54,6 +54,11 @@ If the output is not quite correct, check for invisible trailing spaces!
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</release>
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<release version="4.0" date="XXXX-XX-XX" description="">
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<action dev="psteitz" type="fix" issue="MATH-1245">
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Fixed error in computing discrete distribution of D statistics for small-sample
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2-sample Kolmogorov-Smirnov tests. Error was causing incorrect p-values returned
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by exactP and monteCarloP methods (used by default for small, mid-size samples).
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</action>
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<action dev="erans" type="update" issue="MATH-1243">
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Refactored implementation of the "miscrosphere projection"
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interpolation algorithm.
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@ -21,6 +21,7 @@ import java.math.BigDecimal;
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import java.util.Arrays;
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import java.util.Iterator;
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import org.apache.commons.math4.util.Precision;
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import org.apache.commons.math4.distribution.RealDistribution;
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import org.apache.commons.math4.exception.InsufficientDataException;
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import org.apache.commons.math4.exception.MathArithmeticException;
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@ -884,6 +885,7 @@ public class KolmogorovSmirnovTest {
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long tail = 0;
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final double[] nSet = new double[n];
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final double[] mSet = new double[m];
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final double tol = 1e-12; // d-values within tol of one another are considered equal
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while (combinationsIterator.hasNext()) {
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// Generate an n-set
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final int[] nSetI = combinationsIterator.next();
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@ -898,9 +900,8 @@ public class KolmogorovSmirnovTest {
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}
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}
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final double curD = kolmogorovSmirnovStatistic(nSet, mSet);
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if (curD > d) {
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tail++;
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} else if (curD == d && !strict) {
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final int order = Precision.compareTo(curD, d, tol);
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if (order > 0 || (order == 0 && !strict)) {
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tail++;
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}
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}
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@ -958,6 +959,7 @@ public class KolmogorovSmirnovTest {
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final int nn = FastMath.max(n, m);
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final int mm = FastMath.min(n, m);
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final int sum = nn + mm;
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final double tol = 1e-12; // d-values within tol of one another are considered equal
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int tail = 0;
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final boolean b[] = new boolean[sum];
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@ -979,7 +981,8 @@ public class KolmogorovSmirnovTest {
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final double cdf_n = rankN / (double) nn;
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final double cdf_m = rankM / (double) mm;
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final double curD = FastMath.abs(cdf_n - cdf_m);
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if (curD > d || (curD == d && !strict)) {
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final int order = Precision.compareTo(curD, d, tol);
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if (order > 0 || (order == 0 && !strict)) {
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tail++;
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break;
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}
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@ -427,6 +427,57 @@ public class KolmogorovSmirnovTestTest {
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Assert.assertEquals(1.0, test.approximateP(0, values.length, values.length), 0.);
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}
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}
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/**
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* JIRA: MATH-1245
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*
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* Verify that D-values are not viewed as distinct when they are mathematically equal
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* when computing p-statistics for small sample tests. Reference values are from R 3.2.0.
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*/
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@Test
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public void testDRounding() {
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final double tol = 1e-12;
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final double[] x = {0, 2, 3, 4, 5, 6, 7, 8, 9, 12};
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final double[] y = {1, 10, 11, 13, 14, 15, 16, 17, 18};
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final KolmogorovSmirnovTest test = new KolmogorovSmirnovTest();
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Assert.assertEquals(0.0027495724090154106, test.kolmogorovSmirnovTest(x, y,false), tol);
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final double[] x1 = {2, 4, 6, 8, 9, 10, 11, 12, 13};
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final double[] y1 = {0, 1, 3, 5, 7};
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Assert.assertEquals(0.085914085914085896, test.kolmogorovSmirnovTest(x1, y1, false), tol);
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final double[] x2 = {4, 6, 7, 8, 9, 10, 11};
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final double[] y2 = {0, 1, 2, 3, 5};
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Assert.assertEquals(0.015151515151515027, test.kolmogorovSmirnovTest(x2, y2, false), tol);
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}
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/**
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* JIRA: MATH-1245
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*
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* Verify that D-values are not viewed as distinct when they are mathematically equal
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* when computing p-statistics for small sample tests. Reference values are from R 3.2.0.
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*/
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@Test
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public void testDRoundingMonteCarlo() {
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final double tol = 1e-2;
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final int iterations = 1000000;
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final KolmogorovSmirnovTest test = new KolmogorovSmirnovTest(new Well19937c(1000));
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final double[] x = {0, 2, 3, 4, 5, 6, 7, 8, 9, 12};
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final double[] y = {1, 10, 11, 13, 14, 15, 16, 17, 18};
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double d = test.kolmogorovSmirnovStatistic(x, y);
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Assert.assertEquals(0.0027495724090154106, test.monteCarloP(d, x.length, y.length, false, iterations), tol);
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final double[] x1 = {2, 4, 6, 8, 9, 10, 11, 12, 13};
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final double[] y1 = {0, 1, 3, 5, 7};
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d = test.kolmogorovSmirnovStatistic(x1, y1);
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Assert.assertEquals(0.085914085914085896, test.monteCarloP(d, x1.length, y1.length, false, iterations), tol);
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final double[] x2 = {4, 6, 7, 8, 9, 10, 11};
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final double[] y2 = {0, 1, 2, 3, 5};
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d = test.kolmogorovSmirnovStatistic(x2, y2);
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Assert.assertEquals(0.015151515151515027, test.monteCarloP(d, x2.length, y2.length, false, iterations), tol);
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}
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/**
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* Verifies the inequality exactP(criticalValue, n, m, true) < alpha < exactP(criticalValue, n,
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