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

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

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

        Assert.assertEquals("ANOVA P-value", 6.959446E-06,
                 testStatistic.anovaPValue(threeClasses, true), 1E-12);
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            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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        final SummaryStatistics normal = new SummaryStatistics(); // considered as reference
        final OptimizedStatistics optimized = new OptimizedStatistics();

        for (int i = 0; i < 100; i++) {
            final double value = Math.random() * 100;
            normal.addValue(value);
            optimized.addValue(value);

            doAssert(normal, optimized); // important to assert for 0, 1 and n > 1
        }
    }
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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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            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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        final int len = methods.length;
        final StatisticalSummary[] stats = new StatisticalSummary[len];
        for (int j = 0; j < len; j++) {
            final SummaryStatistics s = new SummaryStatistics();
            for (int k = 0; k < repeatStat; k++) {
                s.addValue(times[j][k][0]);
            }
            stats[j] = s.getSummary();
        }

        return stats;
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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,
                testStatistic.t(mu, observed), 10E-10);
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