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Renamed o.h.stat.inference.TestUtils to InferenceTestUtils

This commit is contained in:
Phil Steitz 2016-08-05 14:25:35 +02:00 committed by Emmanuel Bourg
parent dccc125541
commit 5c341d9ded
3 changed files with 106 additions and 109 deletions
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4
src/main/java/org/apache/commons/math4/stat/inference/TestUtils.java → src/main/java/org/apache/commons/math4/stat/inference/InferenceTestUtils.java
View File

@ -38,7 +38,7 @@ import org.apache.commons.math4.stat.descriptive.StatisticalSummary;
*
* @since 1.1
*/
public class TestUtils {
public class InferenceTestUtils {
/** Singleton TTest instance. */
private static final TTest T_TEST = new TTest();
@ -58,7 +58,7 @@ public class TestUtils {
/**
* Prevent instantiation.
*/
private TestUtils() {
private InferenceTestUtils() {
super();
}

7
src/test/java/org/apache/commons/math4/distribution/BetaDistributionTest.java
View File

@ -18,12 +18,11 @@ package org.apache.commons.math4.distribution;
import java.util.Arrays;
import org.apache.commons.math4.distribution.BetaDistribution;
import org.apache.commons.math4.rng.RandomSource;
import org.apache.commons.math4.rng.UniformRandomProvider;
import org.apache.commons.math4.stat.StatUtils;
import org.apache.commons.math4.stat.inference.KolmogorovSmirnovTest;
import org.apache.commons.math4.stat.inference.TestUtils;
import org.apache.commons.math4.stat.inference.InferenceTestUtils;
import org.junit.Assert;
import org.junit.Test;
@ -325,7 +324,7 @@ public class BetaDistributionTest {
for (final double beta : alphaBetas) {
final BetaDistribution betaDistribution = new BetaDistribution(alpha, beta);
final double[] observed = AbstractRealDistribution.sample(numSamples,
betaDistribution.createSampler(rng));
betaDistribution.createSampler(rng));
Arrays.sort(observed);
final String distribution = String.format("Beta(%.2f, %.2f)", alpha, beta);
@ -380,6 +379,6 @@ public class BetaDistributionTest {
final double[] expected = new double[numBins];
Arrays.fill(expected, (double) values.length / numBins);
return TestUtils.gTest(expected, observed);
return InferenceTestUtils.gTest(expected, observed);
}
}

204
src/test/java/org/apache/commons/math4/stat/inference/TestUtilsTest.java → src/test/java/org/apache/commons/math4/stat/inference/InferenceTestUtilsTest.java
View File

@ -27,8 +27,6 @@ import org.apache.commons.math4.exception.NullArgumentException;
import org.apache.commons.math4.exception.NumberIsTooSmallException;
import org.apache.commons.math4.exception.OutOfRangeException;
import org.apache.commons.math4.stat.descriptive.SummaryStatistics;
import org.apache.commons.math4.stat.inference.OneWayAnova;
import org.apache.commons.math4.stat.inference.TestUtils;
import org.apache.commons.math4.util.FastMath;
import org.junit.Assert;
import org.junit.Test;
@ -38,7 +36,7 @@ import org.junit.Test;
* Test cases for the TestUtils class.
*
*/
public class TestUtilsTest {
public class InferenceTestUtilsTest {
@Test
public void testChiSquare() {
@ -50,18 +48,18 @@ public class TestUtilsTest {
long[] observed = {10, 9, 11};
double[] expected = {10, 10, 10};
Assert.assertEquals("chi-square statistic", 0.2, TestUtils.chiSquare(expected, observed), 10E-12);
Assert.assertEquals("chi-square p-value", 0.904837418036, TestUtils.chiSquareTest(expected, observed), 1E-10);
Assert.assertEquals("chi-square statistic", 0.2, InferenceTestUtils.chiSquare(expected, observed), 10E-12);
Assert.assertEquals("chi-square p-value", 0.904837418036, InferenceTestUtils.chiSquareTest(expected, observed), 1E-10);
long[] observed1 = { 500, 623, 72, 70, 31 };
double[] expected1 = { 485, 541, 82, 61, 37 };
Assert.assertEquals( "chi-square test statistic", 9.023307936427388, TestUtils.chiSquare(expected1, observed1), 1E-10);
Assert.assertEquals("chi-square p-value", 0.06051952647453607, TestUtils.chiSquareTest(expected1, observed1), 1E-9);
Assert.assertTrue("chi-square test reject", TestUtils.chiSquareTest(expected1, observed1, 0.07));
Assert.assertTrue("chi-square test accept", !TestUtils.chiSquareTest(expected1, observed1, 0.05));
Assert.assertEquals( "chi-square test statistic", 9.023307936427388, InferenceTestUtils.chiSquare(expected1, observed1), 1E-10);
Assert.assertEquals("chi-square p-value", 0.06051952647453607, InferenceTestUtils.chiSquareTest(expected1, observed1), 1E-9);
Assert.assertTrue("chi-square test reject", InferenceTestUtils.chiSquareTest(expected1, observed1, 0.07));
Assert.assertTrue("chi-square test accept", !InferenceTestUtils.chiSquareTest(expected1, observed1, 0.05));
try {
TestUtils.chiSquareTest(expected1, observed1, 95);
InferenceTestUtils.chiSquareTest(expected1, observed1, 95);
Assert.fail("alpha out of range, OutOfRangeException expected");
} catch (OutOfRangeException ex) {
// expected
@ -70,7 +68,7 @@ public class TestUtilsTest {
long[] tooShortObs = { 0 };
double[] tooShortEx = { 1 };
try {
TestUtils.chiSquare(tooShortEx, tooShortObs);
InferenceTestUtils.chiSquare(tooShortEx, tooShortObs);
Assert.fail("arguments too short, DimensionMismatchException expected");
} catch (DimensionMismatchException ex) {
// expected
@ -80,7 +78,7 @@ public class TestUtilsTest {
long[] unMatchedObs = { 0, 1, 2, 3 };
double[] unMatchedEx = { 1, 1, 2 };
try {
TestUtils.chiSquare(unMatchedEx, unMatchedObs);
InferenceTestUtils.chiSquare(unMatchedEx, unMatchedObs);
Assert.fail("arrays have different lengths, DimensionMismatchException expected");
} catch (DimensionMismatchException ex) {
// expected
@ -89,7 +87,7 @@ public class TestUtilsTest {
// 0 expected count
expected[0] = 0;
try {
TestUtils.chiSquareTest(expected, observed, .01);
InferenceTestUtils.chiSquareTest(expected, observed, .01);
Assert.fail("bad expected count, NotStrictlyPositiveException expected");
} catch (NotStrictlyPositiveException ex) {
// expected
@ -99,7 +97,7 @@ public class TestUtilsTest {
expected[0] = 1;
observed[0] = -1;
try {
TestUtils.chiSquareTest(expected, observed, .01);
InferenceTestUtils.chiSquareTest(expected, observed, .01);
Assert.fail("bad expected count, NotPositiveException expected");
} catch (NotPositiveException ex) {
// expected
@ -113,20 +111,20 @@ public class TestUtilsTest {
// Target values computed using R version 1.8.1
long[][] counts = { {40, 22, 43}, {91, 21, 28}, {60, 10, 22}};
Assert.assertEquals( "chi-square test statistic", 22.709027688, TestUtils.chiSquare(counts), 1E-9);
Assert.assertEquals("chi-square p-value", 0.000144751460134, TestUtils.chiSquareTest(counts), 1E-9);
Assert.assertTrue("chi-square test reject", TestUtils.chiSquareTest(counts, 0.0002));
Assert.assertTrue("chi-square test accept", !TestUtils.chiSquareTest(counts, 0.0001));
Assert.assertEquals( "chi-square test statistic", 22.709027688, InferenceTestUtils.chiSquare(counts), 1E-9);
Assert.assertEquals("chi-square p-value", 0.000144751460134, InferenceTestUtils.chiSquareTest(counts), 1E-9);
Assert.assertTrue("chi-square test reject", InferenceTestUtils.chiSquareTest(counts, 0.0002));
Assert.assertTrue("chi-square test accept", !InferenceTestUtils.chiSquareTest(counts, 0.0001));
long[][] counts2 = {{10, 15}, {30, 40}, {60, 90} };
Assert.assertEquals( "chi-square test statistic", 0.168965517241, TestUtils.chiSquare(counts2), 1E-9);
Assert.assertEquals("chi-square p-value",0.918987499852, TestUtils.chiSquareTest(counts2), 1E-9);
Assert.assertTrue("chi-square test accept", !TestUtils.chiSquareTest(counts2, 0.1));
Assert.assertEquals( "chi-square test statistic", 0.168965517241, InferenceTestUtils.chiSquare(counts2), 1E-9);
Assert.assertEquals("chi-square p-value",0.918987499852, InferenceTestUtils.chiSquareTest(counts2), 1E-9);
Assert.assertTrue("chi-square test accept", !InferenceTestUtils.chiSquareTest(counts2, 0.1));
// ragged input array
long[][] counts3 = { {40, 22, 43}, {91, 21, 28}, {60, 10}};
try {
TestUtils.chiSquare(counts3);
InferenceTestUtils.chiSquare(counts3);
Assert.fail("Expecting DimensionMismatchException");
} catch (DimensionMismatchException ex) {
// expected
@ -135,14 +133,14 @@ public class TestUtilsTest {
// insufficient data
long[][] counts4 = {{40, 22, 43}};
try {
TestUtils.chiSquare(counts4);
InferenceTestUtils.chiSquare(counts4);
Assert.fail("Expecting DimensionMismatchException");
} catch (DimensionMismatchException ex) {
// expected
}
long[][] counts5 = {{40}, {40}, {30}, {10}};
try {
TestUtils.chiSquare(counts5);
InferenceTestUtils.chiSquare(counts5);
Assert.fail("Expecting DimensionMismatchException");
} catch (DimensionMismatchException ex) {
// expected
@ -151,7 +149,7 @@ public class TestUtilsTest {
// negative counts
long[][] counts6 = {{10, -2}, {30, 40}, {60, 90} };
try {
TestUtils.chiSquare(counts6);
InferenceTestUtils.chiSquare(counts6);
Assert.fail("Expecting NotPositiveException");
} catch (NotPositiveException ex) {
// expected
@ -159,7 +157,7 @@ public class TestUtilsTest {
// bad alpha
try {
TestUtils.chiSquareTest(counts, 0);
InferenceTestUtils.chiSquareTest(counts, 0);
Assert.fail("Expecting OutOfRangeException");
} catch (OutOfRangeException ex) {
// expected
@ -181,7 +179,7 @@ public class TestUtilsTest {
double cst = csti.chiSquareTest(exp, obs);
Assert.assertEquals("chi-square p-value", 0.0, cst, 1E-3);
Assert.assertEquals( "chi-square test statistic",
114875.90421929007, TestUtils.chiSquare(exp, obs), 1E-9);
114875.90421929007, InferenceTestUtils.chiSquare(exp, obs), 1E-9);
}
/** Contingency table containing zeros - PR # 32531 */
@ -190,9 +188,9 @@ public class TestUtilsTest {
// Target values computed using R version 1.8.1
long[][] counts = { {40, 0, 4}, {91, 1, 2}, {60, 2, 0}};
Assert.assertEquals( "chi-square test statistic", 9.67444662263,
TestUtils.chiSquare(counts), 1E-9);
InferenceTestUtils.chiSquare(counts), 1E-9);
Assert.assertEquals("chi-square p-value", 0.0462835770603,
TestUtils.chiSquareTest(counts), 1E-9);
InferenceTestUtils.chiSquareTest(counts), 1E-9);
}
private double[] tooShortObs = { 1.0 };
@ -212,63 +210,63 @@ public class TestUtilsTest {
// Target comparison values computed using R version 1.8.1 (Linux version)
Assert.assertEquals("t statistic", -2.81976445346,
TestUtils.t(mu, observed), 10E-10);
InferenceTestUtils.t(mu, observed), 10E-10);
Assert.assertEquals("t statistic", -2.81976445346,
TestUtils.t(mu, sampleStats), 10E-10);
InferenceTestUtils.t(mu, sampleStats), 10E-10);
Assert.assertEquals("p value", 0.0136390585873,
TestUtils.tTest(mu, observed), 10E-10);
InferenceTestUtils.tTest(mu, observed), 10E-10);
Assert.assertEquals("p value", 0.0136390585873,
TestUtils.tTest(mu, sampleStats), 10E-10);
InferenceTestUtils.tTest(mu, sampleStats), 10E-10);
try {
TestUtils.t(mu, (double[]) null);
InferenceTestUtils.t(mu, (double[]) null);
Assert.fail("arguments too short, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
}
try {
TestUtils.t(mu, (SummaryStatistics) null);
InferenceTestUtils.t(mu, (SummaryStatistics) null);
Assert.fail("arguments too short, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
}
try {
TestUtils.t(mu, emptyObs);
InferenceTestUtils.t(mu, emptyObs);
Assert.fail("arguments too short, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.t(mu, emptyStats);
InferenceTestUtils.t(mu, emptyStats);
Assert.fail("arguments too short, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.t(mu, tooShortObs);
InferenceTestUtils.t(mu, tooShortObs);
Assert.fail("insufficient data to compute t statistic, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.tTest(mu, tooShortObs);
InferenceTestUtils.tTest(mu, tooShortObs);
Assert.fail("insufficient data to perform t test, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.t(mu, (SummaryStatistics) null);
InferenceTestUtils.t(mu, (SummaryStatistics) null);
Assert.fail("insufficient data to compute t statistic, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
}
try {
TestUtils.tTest(mu, (SummaryStatistics) null);
InferenceTestUtils.tTest(mu, (SummaryStatistics) null);
Assert.fail("insufficient data to perform t test, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
@ -285,27 +283,27 @@ public class TestUtilsTest {
}
// Target comparison values computed using R version 1.8.1 (Linux version)
Assert.assertEquals("one sample t stat", 3.86485535541,
TestUtils.t(0d, oneSidedP), 10E-10);
InferenceTestUtils.t(0d, oneSidedP), 10E-10);
Assert.assertEquals("one sample t stat", 3.86485535541,
TestUtils.t(0d, oneSidedPStats),1E-10);
InferenceTestUtils.t(0d, oneSidedPStats),1E-10);
Assert.assertEquals("one sample p value", 0.000521637019637,
TestUtils.tTest(0d, oneSidedP) / 2d, 10E-10);
InferenceTestUtils.tTest(0d, oneSidedP) / 2d, 10E-10);
Assert.assertEquals("one sample p value", 0.000521637019637,
TestUtils.tTest(0d, oneSidedPStats) / 2d, 10E-5);
Assert.assertTrue("one sample t-test reject", TestUtils.tTest(0d, oneSidedP, 0.01));
Assert.assertTrue("one sample t-test reject", TestUtils.tTest(0d, oneSidedPStats, 0.01));
Assert.assertTrue("one sample t-test accept", !TestUtils.tTest(0d, oneSidedP, 0.0001));
Assert.assertTrue("one sample t-test accept", !TestUtils.tTest(0d, oneSidedPStats, 0.0001));
InferenceTestUtils.tTest(0d, oneSidedPStats) / 2d, 10E-5);
Assert.assertTrue("one sample t-test reject", InferenceTestUtils.tTest(0d, oneSidedP, 0.01));
Assert.assertTrue("one sample t-test reject", InferenceTestUtils.tTest(0d, oneSidedPStats, 0.01));
Assert.assertTrue("one sample t-test accept", !InferenceTestUtils.tTest(0d, oneSidedP, 0.0001));
Assert.assertTrue("one sample t-test accept", !InferenceTestUtils.tTest(0d, oneSidedPStats, 0.0001));
try {
TestUtils.tTest(0d, oneSidedP, 95);
InferenceTestUtils.tTest(0d, oneSidedP, 95);
Assert.fail("alpha out of range, OutOfRangeException expected");
} catch (OutOfRangeException ex) {
// expected
}
try {
TestUtils.tTest(0d, oneSidedPStats, 95);
InferenceTestUtils.tTest(0d, oneSidedPStats, 95);
Assert.fail("alpha out of range, OutOfRangeException expected");
} catch (OutOfRangeException ex) {
// expected
@ -328,73 +326,73 @@ public class TestUtilsTest {
// Target comparison values computed using R version 1.8.1 (Linux version)
Assert.assertEquals("two sample heteroscedastic t stat", 1.60371728768,
TestUtils.t(sample1, sample2), 1E-10);
InferenceTestUtils.t(sample1, sample2), 1E-10);
Assert.assertEquals("two sample heteroscedastic t stat", 1.60371728768,
TestUtils.t(sampleStats1, sampleStats2), 1E-10);
InferenceTestUtils.t(sampleStats1, sampleStats2), 1E-10);
Assert.assertEquals("two sample heteroscedastic p value", 0.128839369622,
TestUtils.tTest(sample1, sample2), 1E-10);
InferenceTestUtils.tTest(sample1, sample2), 1E-10);
Assert.assertEquals("two sample heteroscedastic p value", 0.128839369622,
TestUtils.tTest(sampleStats1, sampleStats2), 1E-10);
InferenceTestUtils.tTest(sampleStats1, sampleStats2), 1E-10);
Assert.assertTrue("two sample heteroscedastic t-test reject",
TestUtils.tTest(sample1, sample2, 0.2));
InferenceTestUtils.tTest(sample1, sample2, 0.2));
Assert.assertTrue("two sample heteroscedastic t-test reject",
TestUtils.tTest(sampleStats1, sampleStats2, 0.2));
InferenceTestUtils.tTest(sampleStats1, sampleStats2, 0.2));
Assert.assertTrue("two sample heteroscedastic t-test accept",
!TestUtils.tTest(sample1, sample2, 0.1));
!InferenceTestUtils.tTest(sample1, sample2, 0.1));
Assert.assertTrue("two sample heteroscedastic t-test accept",
!TestUtils.tTest(sampleStats1, sampleStats2, 0.1));
!InferenceTestUtils.tTest(sampleStats1, sampleStats2, 0.1));
try {
TestUtils.tTest(sample1, sample2, .95);
InferenceTestUtils.tTest(sample1, sample2, .95);
Assert.fail("alpha out of range, OutOfRangeException expected");
} catch (OutOfRangeException ex) {
// expected
}
try {
TestUtils.tTest(sampleStats1, sampleStats2, .95);
InferenceTestUtils.tTest(sampleStats1, sampleStats2, .95);
Assert.fail("alpha out of range, OutOfRangeException expected");
} catch (OutOfRangeException ex) {
// expected
}
try {
TestUtils.tTest(sample1, tooShortObs, .01);
InferenceTestUtils.tTest(sample1, tooShortObs, .01);
Assert.fail("insufficient data, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.tTest(sampleStats1, (SummaryStatistics) null, .01);
InferenceTestUtils.tTest(sampleStats1, (SummaryStatistics) null, .01);
Assert.fail("insufficient data, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
}
try {
TestUtils.tTest(sample1, tooShortObs);
InferenceTestUtils.tTest(sample1, tooShortObs);
Assert.fail("insufficient data, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.tTest(sampleStats1, (SummaryStatistics) null);
InferenceTestUtils.tTest(sampleStats1, (SummaryStatistics) null);
Assert.fail("insufficient data, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
}
try {
TestUtils.t(sample1, tooShortObs);
InferenceTestUtils.t(sample1, tooShortObs);
Assert.fail("insufficient data, NumberIsTooSmallException expected");
} catch (NumberIsTooSmallException ex) {
// expected
}
try {
TestUtils.t(sampleStats1, (SummaryStatistics) null);
InferenceTestUtils.t(sampleStats1, (SummaryStatistics) null);
Assert.fail("insufficient data, NullArgumentException expected");
} catch (NullArgumentException ex) {
// expected
@ -415,13 +413,13 @@ public class TestUtilsTest {
// Target comparison values computed using R version 1.8.1 (Linux version)
Assert.assertEquals("two sample homoscedastic t stat", 0.73096310086,
TestUtils.homoscedasticT(sample1, sample2), 10E-11);
InferenceTestUtils.homoscedasticT(sample1, sample2), 10E-11);
Assert.assertEquals("two sample homoscedastic p value", 0.4833963785,
TestUtils.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10);
InferenceTestUtils.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10);
Assert.assertTrue("two sample homoscedastic t-test reject",
TestUtils.homoscedasticTTest(sample1, sample2, 0.49));
InferenceTestUtils.homoscedasticTTest(sample1, sample2, 0.49));
Assert.assertTrue("two sample homoscedastic t-test accept",
!TestUtils.homoscedasticTTest(sample1, sample2, 0.48));
!InferenceTestUtils.homoscedasticTTest(sample1, sample2, 0.48));
}
@Test
@ -430,9 +428,9 @@ public class TestUtilsTest {
double[] sample2 = {4d, 5d};
// Target values computed using R, version 1.8.1 (linux version)
Assert.assertEquals(-2.2360679775, TestUtils.t(sample1, sample2),
Assert.assertEquals(-2.2360679775, InferenceTestUtils.t(sample1, sample2),
1E-10);
Assert.assertEquals(0.198727388935, TestUtils.tTest(sample1, sample2),
Assert.assertEquals(0.198727388935, InferenceTestUtils.tTest(sample1, sample2),
1E-10);
}
@ -443,11 +441,11 @@ public class TestUtilsTest {
double[] sample3 = {5d, 7d, 8d, 10d};
// Target values computed using R, version 1.8.1 (linux version)
Assert.assertEquals(-0.3133, TestUtils.pairedT(sample1, sample2), 1E-4);
Assert.assertEquals(0.774544295819, TestUtils.pairedTTest(sample1, sample2), 1E-10);
Assert.assertEquals(0.001208, TestUtils.pairedTTest(sample1, sample3), 1E-6);
Assert.assertFalse(TestUtils.pairedTTest(sample1, sample3, .001));
Assert.assertTrue(TestUtils.pairedTTest(sample1, sample3, .002));
Assert.assertEquals(-0.3133, InferenceTestUtils.pairedT(sample1, sample2), 1E-4);
Assert.assertEquals(0.774544295819, InferenceTestUtils.pairedTTest(sample1, sample2), 1E-10);
Assert.assertEquals(0.001208, InferenceTestUtils.pairedTTest(sample1, sample3), 1E-6);
Assert.assertFalse(InferenceTestUtils.pairedTTest(sample1, sample3, .001));
Assert.assertTrue(InferenceTestUtils.pairedTTest(sample1, sample3, .002));
}
private double[] classA =
@ -466,11 +464,11 @@ public class TestUtilsTest {
classes.add(classB);
classes.add(classC);
Assert.assertEquals(oneWayAnova.anovaFValue(classes),
TestUtils.oneWayAnovaFValue(classes), 10E-12);
InferenceTestUtils.oneWayAnovaFValue(classes), 10E-12);
Assert.assertEquals(oneWayAnova.anovaPValue(classes),
TestUtils.oneWayAnovaPValue(classes), 10E-12);
InferenceTestUtils.oneWayAnovaPValue(classes), 10E-12);
Assert.assertEquals(oneWayAnova.anovaTest(classes, 0.01),
TestUtils.oneWayAnovaTest(classes, 0.01));
InferenceTestUtils.oneWayAnovaTest(classes, 0.01));
}
@Test
public void testGTestGoodnesOfFit() throws Exception {
@ -482,11 +480,11 @@ public class TestUtilsTest {
70, 79, 3, 4
};
Assert.assertEquals("G test statistic",
13.144799, TestUtils.g(exp, obs), 1E-5);
double p_gtgf = TestUtils.gTest(exp, obs);
13.144799, InferenceTestUtils.g(exp, obs), 1E-5);
double p_gtgf = InferenceTestUtils.gTest(exp, obs);
Assert.assertEquals("g-Test p-value", 0.004333, p_gtgf, 1E-5);
Assert.assertTrue(TestUtils.gTest(exp, obs, 0.05));
Assert.assertTrue(InferenceTestUtils.gTest(exp, obs, 0.05));
}
@Test
@ -499,36 +497,36 @@ public class TestUtilsTest {
807, 759, 184
};
double g = TestUtils.gDataSetsComparison(obs1, obs2);
double g = InferenceTestUtils.gDataSetsComparison(obs1, obs2);
Assert.assertEquals("G test statistic",
7.3008170, g, 1E-4);
double p_gti = TestUtils.gTestDataSetsComparison(obs1, obs2);
double p_gti = InferenceTestUtils.gTestDataSetsComparison(obs1, obs2);
Assert.assertEquals("g-Test p-value", 0.0259805, p_gti, 1E-4);
Assert.assertTrue(TestUtils.gTestDataSetsComparison(obs1, obs2, 0.05));
Assert.assertTrue(InferenceTestUtils.gTestDataSetsComparison(obs1, obs2, 0.05));
}
@Test
public void testRootLogLikelihood() {
// positive where k11 is bigger than expected.
Assert.assertTrue(TestUtils.rootLogLikelihoodRatio(904, 21060, 1144, 283012) > 0.0);
Assert.assertTrue(InferenceTestUtils.rootLogLikelihoodRatio(904, 21060, 1144, 283012) > 0.0);
// negative because k11 is lower than expected
Assert.assertTrue(TestUtils.rootLogLikelihoodRatio(36, 21928, 60280, 623876) < 0.0);
Assert.assertTrue(InferenceTestUtils.rootLogLikelihoodRatio(36, 21928, 60280, 623876) < 0.0);
Assert.assertEquals(FastMath.sqrt(2.772589), TestUtils.rootLogLikelihoodRatio(1, 0, 0, 1), 0.000001);
Assert.assertEquals(-FastMath.sqrt(2.772589), TestUtils.rootLogLikelihoodRatio(0, 1, 1, 0), 0.000001);
Assert.assertEquals(FastMath.sqrt(27.72589), TestUtils.rootLogLikelihoodRatio(10, 0, 0, 10), 0.00001);
Assert.assertEquals(FastMath.sqrt(2.772589), InferenceTestUtils.rootLogLikelihoodRatio(1, 0, 0, 1), 0.000001);
Assert.assertEquals(-FastMath.sqrt(2.772589), InferenceTestUtils.rootLogLikelihoodRatio(0, 1, 1, 0), 0.000001);
Assert.assertEquals(FastMath.sqrt(27.72589), InferenceTestUtils.rootLogLikelihoodRatio(10, 0, 0, 10), 0.00001);
Assert.assertEquals(FastMath.sqrt(39.33052), TestUtils.rootLogLikelihoodRatio(5, 1995, 0, 100000), 0.00001);
Assert.assertEquals(-FastMath.sqrt(39.33052), TestUtils.rootLogLikelihoodRatio(0, 100000, 5, 1995), 0.00001);
Assert.assertEquals(FastMath.sqrt(39.33052), InferenceTestUtils.rootLogLikelihoodRatio(5, 1995, 0, 100000), 0.00001);
Assert.assertEquals(-FastMath.sqrt(39.33052), InferenceTestUtils.rootLogLikelihoodRatio(0, 100000, 5, 1995), 0.00001);
Assert.assertEquals(FastMath.sqrt(4730.737), TestUtils.rootLogLikelihoodRatio(1000, 1995, 1000, 100000), 0.001);
Assert.assertEquals(-FastMath.sqrt(4730.737), TestUtils.rootLogLikelihoodRatio(1000, 100000, 1000, 1995), 0.001);
Assert.assertEquals(FastMath.sqrt(4730.737), InferenceTestUtils.rootLogLikelihoodRatio(1000, 1995, 1000, 100000), 0.001);
Assert.assertEquals(-FastMath.sqrt(4730.737), InferenceTestUtils.rootLogLikelihoodRatio(1000, 100000, 1000, 1995), 0.001);
Assert.assertEquals(FastMath.sqrt(5734.343), TestUtils.rootLogLikelihoodRatio(1000, 1000, 1000, 100000), 0.001);
Assert.assertEquals(FastMath.sqrt(5714.932), TestUtils.rootLogLikelihoodRatio(1000, 1000, 1000, 99000), 0.001);
Assert.assertEquals(FastMath.sqrt(5734.343), InferenceTestUtils.rootLogLikelihoodRatio(1000, 1000, 1000, 100000), 0.001);
Assert.assertEquals(FastMath.sqrt(5714.932), InferenceTestUtils.rootLogLikelihoodRatio(1000, 1000, 1000, 99000), 0.001);
}
@Test
@ -536,8 +534,8 @@ public class TestUtilsTest {
final NormalDistribution unitNormal = new NormalDistribution(0d, 1d);
final double[] sample = KolmogorovSmirnovTestTest.gaussian;
final double tol = KolmogorovSmirnovTestTest.TOLERANCE;
Assert.assertEquals(0.3172069207622391, TestUtils.kolmogorovSmirnovTest(unitNormal, sample), tol);
Assert.assertEquals(0.0932947561266756, TestUtils.kolmogorovSmirnovStatistic(unitNormal, sample), tol);
Assert.assertEquals(0.3172069207622391, InferenceTestUtils.kolmogorovSmirnovTest(unitNormal, sample), tol);
Assert.assertEquals(0.0932947561266756, InferenceTestUtils.kolmogorovSmirnovStatistic(unitNormal, sample), tol);
}
@Test
@ -550,10 +548,10 @@ public class TestUtilsTest {
10, 11, 12, 16, 20, 27, 28, 32, 44, 54
};
Assert
.assertEquals(0.105577085453247, TestUtils.kolmogorovSmirnovTest(smallSample1, smallSample2, false), tol);
final double d = TestUtils.kolmogorovSmirnovStatistic(smallSample1, smallSample2);
.assertEquals(0.105577085453247, InferenceTestUtils.kolmogorovSmirnovTest(smallSample1, smallSample2, false), tol);
final double d = InferenceTestUtils.kolmogorovSmirnovStatistic(smallSample1, smallSample2);
Assert.assertEquals(0.5, d, tol);
Assert
.assertEquals(0.105577085453247, TestUtils.exactP(d, smallSample1.length,smallSample2.length, false), tol);
.assertEquals(0.105577085453247, InferenceTestUtils.exactP(d, smallSample1.length, smallSample2.length, false), tol);
}
}