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

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

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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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    } catch (IllegalArgumentException ex) {
      // ignored
    }
    SummaryStatistics u = new SummaryStatistics();
    for (int i = 0; i < largeSampleSize; i++) {
      u.addValue(randomData.nextGaussian(0, 1));
    }
    double xbar = u.getMean();
    double s = u.getStandardDeviation();
    double n = u.getN();
    /*

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    @Test
    public void testGaussian() {
        MersenneTwister mt = new MersenneTwister(42853252100l);
        SummaryStatistics sample = new SummaryStatistics();
        for (int i = 0; i < 1000; ++i) {
            sample.addValue(mt.nextGaussian());
        }
        assertEquals(0.0, sample.getMean(), 0.005);
        assertEquals(1.0, sample.getStandardDeviation(), 0.025);
    }

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    @Test
    public void testDouble() {
        MersenneTwister mt = new MersenneTwister(195357343514l);
        SummaryStatistics sample = new SummaryStatistics();
        for (int i = 0; i < 1000; ++i) {
            sample.addValue(mt.nextDouble());
        }
        assertEquals(0.5, sample.getMean(), 0.02);
        assertEquals(1.0 / (2.0 * Math.sqrt(3.0)),
                     sample.getStandardDeviation(),
                     0.002);

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    public void testTwoSampleTHeterscedastic() throws Exception {
        double[] sample1 = { 7d, -4d, 18d, 17d, -3d, -5d, 1d, 10d, 11d, -2d };
        double[] sample2 = { -1d, 12d, -1d, -3d, 3d, -5d, 5d, 2d, -11d, -1d, -3d };
        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 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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