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

            String str = null;
            double val = 0.0d;
            while ((str = inputStream.readLine()) != null) {
                val = Double.parseDouble(str);
                SummaryStatistics stats = binStats.get(findBin(val));
                stats.addValue(val);
            }


            inputStream.close();
            inputStream = null;
        }

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        @Override
        public void computeBinStats() throws IOException {
            for (int i = 0; i < inputArray.length; i++) {
                SummaryStatistics stats =
                    binStats.get(findBin(inputArray[i]));
                stats.addValue(inputArray[i]);
            }
        }
    }


    /**

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        // 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);

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                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);
                }
            }

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        Assert.assertTrue("empirical distribution property",
            vs.getEmpiricalDistribution() != null);
        SummaryStatistics stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            next = vs.getNext();
            stats.addValue(next);
        }
        Assert.assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);
        Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(),
            tolerance);

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        vs.computeDistribution(500);
        stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            next = vs.getNext();
            stats.addValue(next);
        }
        Assert.assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);
        Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(),
            tolerance);
    }

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        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 heteroscedastic t stat", 1.60371728768,
                testStatistic.t(sample1, sample2), 1E-10);

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    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]);
        }

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        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,
              testStatistic.homoscedasticT(sample1, sample2), 10E-11);

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            {93.0, 103.0, 95.0, 101.0, 91.0, 105.0, 96.0, 94.0, 101.0,  88.0, 98.0, 94.0, 101.0, 92.0, 95.0 };
        double mu = 100.0;
        SummaryStatistics sampleStats = null;
        sampleStats = new SummaryStatistics();
        for (int i = 0; i < observed.length; i++) {
            sampleStats.addValue(observed[i]);
        }


        // Target comparison values computed using R version 1.8.1 (Linux version)
        Assert.assertEquals("t statistic",  -2.81976445346,
                TestUtils.t(mu, observed), 10E-10);

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