Examples of org.apache.commons.math3.stat.descriptive.SummaryStatistics.addValue()

Package org.apache.commons.math3.stat.descriptive

Class org.apache.commons.math3.stat.descriptive.SummaryStatistics

Examples of org.apache.commons.math3.stat.descriptive.SummaryStatistics.addValue()

org.apache.commons.math3.stat.descriptive.SummaryStatistics.addValue()
Add a value to the data @param value the value to add

    public void testTwoSampleTHomoscedastic() {
        double[] sample1 ={2, 4, 6, 8, 10, 97};
        double[] sample2 = {4, 6, 8, 10, 16};
        SummaryStatistics sampleStats1 = new SummaryStatistics();
        for (int i = 0; i < sample1.length; i++) {
            sampleStats1.addValue(sample1[i]);
        }
        SummaryStatistics sampleStats2 = new SummaryStatistics();
        for (int i = 0; i < sample2.length; i++) {
            sampleStats2.addValue(sample2[i]);
        }

View Full Code Here

        for (int i = 0; i < sample1.length; i++) {
            sampleStats1.addValue(sample1[i]);
        }
        SummaryStatistics sampleStats2 = new SummaryStatistics();
        for (int i = 0; i < sample2.length; i++) {
            sampleStats2.addValue(sample2[i]);
        }


        // 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);

View Full Code Here

        // convert arrays to SummaryStatistics
        for (final double[] data : categoryData) {
            final SummaryStatistics dataSummaryStatistics = new SummaryStatistics();
            categoryDataSummaryStatistics.add(dataSummaryStatistics);
            for (final double val : data) {
                dataSummaryStatistics.addValue(val);
            }
        }


        return anovaStats(categoryDataSummaryStatistics, false);

View Full Code Here

    @Test
    public void testDoubleDirect() {
        SummaryStatistics sample = new SummaryStatistics();
        final int N = 10000;
        for (int i = 0; i < N; ++i) {
            sample.addValue(generator.nextDouble());
        }
        Assert.assertEquals("Note: This test will fail randomly about 1 in 100 times.",
                0.5, sample.getMean(), FastMath.sqrt(N/12.0) * 2.576);
        Assert.assertEquals(1.0 / (2.0 * FastMath.sqrt(3.0)),
                     sample.getStandardDeviation(), 0.01);

View Full Code Here

    @Test
    public void testFloatDirect() {
        SummaryStatistics sample = new SummaryStatistics();
        final int N = 1000;
        for (int i = 0; i < N; ++i) {
            sample.addValue(generator.nextFloat());
        }
        Assert.assertEquals("Note: This test will fail randomly about 1 in 100 times.",
                0.5, sample.getMean(), FastMath.sqrt(N/12.0) * 2.576);
        Assert.assertEquals(1.0 / (2.0 * FastMath.sqrt(3.0)),
                     sample.getStandardDeviation(), 0.01);

View Full Code Here

    private void tstGen(double tolerance)throws Exception {
        empiricalDistribution.load(url);
        empiricalDistribution.reSeed(1000);
        SummaryStatistics stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            stats.addValue(empiricalDistribution.getNextValue());
        }
        Assert.assertEquals("mean", 5.069831575018909, stats.getMean(),tolerance);
        Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(),tolerance);
    }

View Full Code Here

    private void tstDoubleGen(double tolerance)throws Exception {
        empiricalDistribution2.load(dataArray);
        empiricalDistribution2.reSeed(1000);
        SummaryStatistics stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            stats.addValue(empiricalDistribution2.getNextValue());
        }
        Assert.assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);
        Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(), tolerance);
    }

View Full Code Here

                errNew = FastMath.abs((actualNew - expected) / ulp);


                if (Double.isNaN(actualOld) || Double.isInfinite(actualOld)) {
                    Assert.assertFalse(msg, Double.isNaN(actualNew));
                    Assert.assertFalse(msg, Double.isInfinite(actualNew));
                    statNewOF.addValue(errNew);
                } else {
                    statOld.addValue(errOld);
                    statNewNoOF.addValue(errNew);
                }
            }

View Full Code Here

    public void testAnovaPValueSummaryStatistics() {
        // Target comparison values computed using R version 2.6.0 (Linux version)
        List<SummaryStatistics> threeClasses = new ArrayList<SummaryStatistics>();
        SummaryStatistics statsA = new SummaryStatistics();
        for (double a : classA) {
            statsA.addValue(a);
        }
        threeClasses.add(statsA);
        SummaryStatistics statsB = new SummaryStatistics();
        for (double b : classB) {
            statsB.addValue(b);

View Full Code Here

            statsA.addValue(a);
        }
        threeClasses.add(statsA);
        SummaryStatistics statsB = new SummaryStatistics();
        for (double b : classB) {
            statsB.addValue(b);
        }
        threeClasses.add(statsB);
        SummaryStatistics statsC = new SummaryStatistics();
        for (double c : classC) {
            statsC.addValue(c);

View Full Code Here

0 1 2 3 4 5 6 7 8 9

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.