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

Package org.apache.commons.math.stat.descriptive

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

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

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

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

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    public void testTwoSampleTHomoscedastic() throws Exception {
        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)
        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)
        assertEquals("t statistic",  -2.81976445346,
                TestUtils.t(mu, observed), 10E-10);

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

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    private void tstDoubleGen(double tolerance)throws Exception {
        empiricalDistribution2.load(dataArray);
        SummaryStatistics stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            stats.addValue(empiricalDistribution2.getNextValue());
        }
        assertEquals("mean", stats.getMean(),5.069831575018909,tolerance);
        assertEquals
         ("std dev", stats.getStandardDeviation(),1.0173699343977738,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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            for ( String path : sharder.getQueuePaths() )
            {
                int numChildren = client.checkExists().forPath(path).getNumChildren();
                Assert.assertTrue(numChildren > 0);
                Assert.assertTrue(numChildren >= (threshold * .1));
                statistics.addValue(numChildren);
            }
            latch.countDown();


            Assert.assertTrue(statistics.getMean() >= (threshold * .9));
        }

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        } catch (IllegalArgumentException ex) {
            ;
        }
        SummaryStatistics u = SummaryStatistics.newInstance();
        for (int i = 0; i<largeSampleSize; i++) {
            u.addValue(randomData.nextGaussian(0,1));
        }
        double xbar = u.getMean();
        double s = u.getStandardDeviation();
        double n = (double) u.getN(); 
        /* t-test at .001-level TODO: replace with externalized t-test, with

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