Package org.apache.commons.math3.stat

Examples of org.apache.commons.math3.stat.Frequency


        // Generate sample values
        final int sampleSize = 1000;        // Number of deviates to generate
        final int minExpectedCount = 7;     // Minimum size of expected bin count
        long maxObservedValue = 0;
        final double alpha = 0.001;         // Probability of false failure
        Frequency frequency = new Frequency();
        for (int i = 0; i < sampleSize; i++) {
            long value = randomData.nextPoisson(mean);
            if (value > maxObservedValue) {
                maxObservedValue = value;
            }
            frequency.addValue(value);
        }

        /*
         *  Set up bins for chi-square test.
         *  Ensure expected counts are all at least minExpectedCount.
         *  Start with upper and lower tail bins.
         *  Lower bin = [0, lower); Upper bin = [upper, +inf).
         */
        PoissonDistribution poissonDistribution = new PoissonDistribution(mean);
        int lower = 1;
        while (poissonDistribution.cumulativeProbability(lower - 1) * sampleSize < minExpectedCount) {
            lower++;
        }
        int upper = (int) (5 * mean)// Even for mean = 1, not much mass beyond 5
        while ((1 - poissonDistribution.cumulativeProbability(upper - 1)) * sampleSize < minExpectedCount) {
            upper--;
        }

        // Set bin width for interior bins.  For poisson, only need to look at end bins.
        int binWidth = 0;
        boolean widthSufficient = false;
        double lowerBinMass = 0;
        double upperBinMass = 0;
        while (!widthSufficient) {
            binWidth++;
            lowerBinMass = poissonDistribution.cumulativeProbability(lower - 1, lower + binWidth - 1);
            upperBinMass = poissonDistribution.cumulativeProbability(upper - binWidth - 1, upper - 1);
            widthSufficient = FastMath.min(lowerBinMass, upperBinMass) * sampleSize >= minExpectedCount;
        }

        /*
         *  Determine interior bin bounds.  Bins are
         *  [1, lower = binBounds[0]), [lower, binBounds[1]), [binBounds[1], binBounds[2]), ... ,
         *    [binBounds[binCount - 2], upper = binBounds[binCount - 1]), [upper, +inf)
         *
         */
        List<Integer> binBounds = new ArrayList<Integer>();
        binBounds.add(lower);
        int bound = lower + binWidth;
        while (bound < upper - binWidth) {
            binBounds.add(bound);
            bound += binWidth;
        }
        binBounds.add(upper); // The size of bin [binBounds[binCount - 2], upper) satisfies binWidth <= size < 2*binWidth.

        // Compute observed and expected bin counts
        final int binCount = binBounds.size() + 1;
        long[] observed = new long[binCount];
        double[] expected = new double[binCount];

        // Bottom bin
        observed[0] = 0;
        for (int i = 0; i < lower; i++) {
            observed[0] += frequency.getCount(i);
        }
        expected[0] = poissonDistribution.cumulativeProbability(lower - 1) * sampleSize;

        // Top bin
        observed[binCount - 1] = 0;
        for (int i = upper; i <= maxObservedValue; i++) {
            observed[binCount - 1] += frequency.getCount(i);
        }
        expected[binCount - 1] = (1 - poissonDistribution.cumulativeProbability(upper - 1)) * sampleSize;

        // Interior bins
        for (int i = 1; i < binCount - 1; i++) {
            observed[i] = 0;
            for (int j = binBounds.get(i - 1); j < binBounds.get(i); j++) {
                observed[i] += frequency.getCount(j);
            } // Expected count is (mass in [binBounds[i-1], binBounds[i])) * sampleSize
            expected[i] = (poissonDistribution.cumulativeProbability(binBounds.get(i) - 1) -
                poissonDistribution.cumulativeProbability(binBounds.get(i - 1) -1)) * sampleSize;
        }

View Full Code Here


            hexString = randomData.nextHexString(0);
            Assert.fail("zero length requested -- expecting MathIllegalArgumentException");
        } catch (MathIllegalArgumentException ex) {
            // ignored
        }
        Frequency f = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            hexString = randomData.nextHexString(100);
            if (hexString.length() != 100) {
                Assert.fail("incorrect length for generated string");
            }
            for (int j = 0; j < hexString.length(); j++) {
                f.addValue(hexString.substring(j, j + 1));
            }
        }
        double[] expected = new double[16];
        long[] observed = new long[16];
        for (int i = 0; i < 16; i++) {
            expected[i] = (double) smallSampleSize * 100 / 16;
            observed[i] = f.getCount(hex[i]);
        }
        TestUtils.assertChiSquareAccept(expected, observed, 0.001);
    }
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            hexString = randomData.nextSecureHexString(0);
            Assert.fail("zero length requested -- expecting MathIllegalArgumentException");
        } catch (MathIllegalArgumentException ex) {
            // ignored
        }
        Frequency f = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            hexString = randomData.nextSecureHexString(100);
            if (hexString.length() != 100) {
                Assert.fail("incorrect length for generated string");
            }
            for (int j = 0; j < hexString.length(); j++) {
                f.addValue(hexString.substring(j, j + 1));
            }
        }
        double[] expected = new double[16];
        long[] observed = new long[16];
        for (int i = 0; i < 16; i++) {
            expected[i] = (double) smallSampleSize * 100 / 16;
            observed[i] = f.getCount(hex[i]);
        }
        TestUtils.assertChiSquareAccept(expected, observed, 0.001);
    }
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        binBounds[0] = min + binSize;
        for (int i = 1; i < binCount - 1; i++) {
            binBounds[i] = binBounds[i - 1] + binSize;  // + instead of * to avoid overflow in extreme case
        }
       
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final double value = randomData.nextUniform(min, max);
            Assert.assertTrue("nextUniform range", (value > min) && (value < max));
            // Find bin
            int j = 0;
            while (j < binCount - 1 && value > binBounds[j]) {
                j++;
            }
            freq.addValue(j);
        }
      
        final long[] observed = new long[binCount];
        for (int i = 0; i < binCount; i++) {
            observed[i] = freq.getCount(i);
        }
        final double[] expected = new double[binCount];
        for (int i = 0; i < binCount; i++) {
            expected[i] = 1d / binCount;
        }
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    public void testNextLongDirect() {
        long q1 = Long.MAX_VALUE/4;
        long q2 = 2 *  q1;
        long q3 = 3 * q1;

        Frequency freq = new Frequency();
        long val = 0;
        int value = 0;
        for (int i=0; i<smallSampleSize; i++) {
            val = generator.nextLong();
            val = val < 0 ? -val : val;
            if (val < q1) {
                value = 0;
            } else if (val < q2) {
                value = 1;
            } else if (val < q3) {
                value = 2;
            } else {
                value = 3;
            }
            freq.addValue(value);
        }
        long[] observed = new long[4];
        for (int i=0; i<4; i++) {
            observed[i] = freq.getCount(i);
        }

        /* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
         * Change to 11.34 for alpha = .01
         */
 
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                testStatistic.chiSquare(expected,observed) < 10.828);
    }

    @Test
    public void testNextFloatDirect() {
        Frequency freq = new Frequency();
        float val = 0;
        int value = 0;
        for (int i=0; i<smallSampleSize; i++) {
            val = generator.nextFloat();
            if (val < 0.25) {
                value = 0;
            } else if (val < 0.5) {
                value = 1;
            } else if (val < 0.75) {
                value = 2;
            } else {
                value = 3;
            }
            freq.addValue(value);
        }
        long[] observed = new long[4];
        for (int i=0; i<4; i++) {
            observed[i] = freq.getCount(i);
        }

        /* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
         * Change to 11.34 for alpha = .01
         */
 
View Full Code Here

        }
    }
   
   
    private void checkNextIntUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final int value = randomData.nextInt(min, max);
            Assert.assertTrue("nextInt range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }
View Full Code Here

            checkNextLongUniform(2, 12);
        }
    }
   
    private void checkNextLongUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final long value = randomData.nextLong(min, max);
            Assert.assertTrue("nextLong range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }
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            checkNextSecureLongUniform(2, 12);
        }
    }
   
    private void checkNextSecureLongUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final long value = randomData.nextSecureLong(min, max);
            Assert.assertTrue("nextLong range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }
View Full Code Here

            checkNextSecureIntUniform(2, 12);
        }
    }
    
    private void checkNextSecureIntUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final int value = randomData.nextSecureInt(min, max);
            Assert.assertTrue("nextInt range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }
View Full Code Here

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