Examples of GammaDistribution

    public void testNextGamma() {
        double[] quartiles;
        long[] counts;


        // Tests shape > 1, one case in the rejection sampling
        quartiles = TestUtils.getDistributionQuartiles(new GammaDistribution(4, 2));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextGamma(4, 2);
            TestUtils.updateCounts(value, counts, quartiles);
        }
        TestUtils.assertChiSquareAccept(expected, counts, 0.001);


        // Tests shape <= 1, another case in the rejection sampling
        quartiles = TestUtils.getDistributionQuartiles(new GammaDistribution(0.3, 3));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextGamma(0.3, 3);
            TestUtils.updateCounts(value, counts, quartiles);

Examples of org.apache.commons.math3.distribution.GammaDistribution

     * @return random value sampled from the Gamma(shape, scale) distribution
     * @throws NotStrictlyPositiveException if {@code shape <= 0} or
     * {@code scale <= 0}.
     */
    public double nextGamma(double shape, double scale) throws NotStrictlyPositiveException {
        return new GammaDistribution(getRandomGenerator(),shape, scale,
                GammaDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }

Examples of org.apache.commons.math3.distribution.GammaDistribution

     * @return random value sampled from the Gamma(shape, scale) distribution
     * @throws NotStrictlyPositiveException if {@code shape <= 0} or
     * {@code scale <= 0}.
     */
    public double nextGamma(double shape, double scale) throws NotStrictlyPositiveException {
        return new GammaDistribution(getRan(),shape, scale,
                GammaDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }

Examples of org.apache.commons.math3.distribution.GammaDistribution

    public void testNextGamma() {
        double[] quartiles;
        long[] counts;


        // Tests shape > 1, one case in the rejection sampling
        quartiles = TestUtils.getDistributionQuartiles(new GammaDistribution(4, 2));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextGamma(4, 2);
            TestUtils.updateCounts(value, counts, quartiles);
        }
        TestUtils.assertChiSquareAccept(expected, counts, 0.001);


        // Tests shape <= 1, another case in the rejection sampling
        quartiles = TestUtils.getDistributionQuartiles(new GammaDistribution(0.3, 3));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextGamma(0.3, 3);
            TestUtils.updateCounts(value, counts, quartiles);

Examples of org.apache.commons.math3.distribution.GammaDistribution

            assertEquals(x3, r.get("v3").get("value").asDouble(), 0);
        }


        // now compare against reference distributions to test accuracy of the observed step distributions
        NormalDistribution normalDistribution = new NormalDistribution();
        GammaDistribution gd1 = new GammaDistribution(0.2, 5);
        GammaDistribution gd2 = new GammaDistribution(1, 1);
        TDistribution tDistribution = new TDistribution(2);
        for (double q : new double[]{0.001, 0.01, 0.1, 0.2, 0.5, 0.8, 0.9, 0.99, 0.99}) {
            double uG1 = gd1.cumulativeProbability(tdG1.quantile(q));
            assertEquals(q, uG1, (1 - q) * q * 10e-2);


            double uG2 = gd2.cumulativeProbability(tdG2.quantile(q));
            assertEquals(q, uG2, (1 - q) * q * 10e-2);


            double u1 = normalDistribution.cumulativeProbability(td1.quantile(q));
            assertEquals(q, u1, (1 - q) * q * 10e-2);

Examples of org.apache.commons.math3.distribution.GammaDistribution

    public void testNextGamma() throws Exception {
        double[] quartiles;
        long[] counts;


        // Tests shape > 1, one case in the rejection sampling
        quartiles = TestUtils.getDistributionQuartiles(new GammaDistribution(4, 2));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextGamma(4, 2);
            TestUtils.updateCounts(value, counts, quartiles);
        }
        TestUtils.assertChiSquareAccept(expected, counts, 0.001);


        // Tests shape <= 1, another case in the rejection sampling
        quartiles = TestUtils.getDistributionQuartiles(new GammaDistribution(0.3, 3));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextGamma(0.3, 3);
            TestUtils.updateCounts(value, counts, quartiles);

Examples of org.jquantlib.math.distributions.GammaDistribution

                  {14.0, 7.665444025768806E-9},
                  {15.0, 2.659774281674882E-9}};


    // Test for a = 1.0 (alpha)
    double a = 1.0;
    final GammaDistribution gammDistribution = new GammaDistribution(a);
    for (final double[] testvalue : testvalues) {
      final double expected = testvalue[1];
      final double x = testvalue[0];
      final double computed = gammDistribution.op(x);
      // QL.info(computed); // for testing
      final double tolerance = 1.0e-15;
      if (Math.abs(expected-computed)>tolerance) {
        fail("x: " + x + " expected: " + expected + " realised: " + computed);
      }
    }


    // Test for a = 0.1 (alpha)
    a = 0.1;
    final GammaDistribution gammDist = new GammaDistribution(a);
    for (final double[] element : testvalues2) {
      final double expected = element[1];
      final double x = element[0];
      final double computed = gammDist.op(x);
      // QL.info(computed); // for testing
      final double tolerance = 1.0e-15;
      if (Math.abs(expected-computed)>tolerance) {
        fail("x: " + x + " expected: " + expected + " realised: " + computed);
      }

Examples of org.jquantlib.math.distributions.GammaDistribution

          return cpd.op(k);


      }


          public static double evaluateGammaDistribution(double a, double x) {
              GammaDistribution gd = new GammaDistribution(a);
              return gd.op(x);
          }