Examples of ExponentialDistribution

    lambdaMax = lambda.getMax();
  }


  @Override
  public ImmutableList<Double> generate(RandomGenerator rng) {
    final ExponentialDistribution ed = new ExponentialDistribution(rng,
        1d / lambdaMax,
        ExponentialDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    double sum = 0d;


    final ImmutableList.Builder<Double> builder = ImmutableList.builder();
    while (sum < length) {
      sum += ed.sample();
      if (sum < length && rng.nextDouble() <= (lambd.apply(sum) / lambdaMax)) {
        builder.add(sum);
      }
    }
    return builder.build();

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

         */
        double[] quartiles;
        long[] counts;


        // Mean 1
        quartiles = TestUtils.getDistributionQuartiles(new ExponentialDistribution(1));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextExponential(1);
            TestUtils.updateCounts(value, counts, quartiles);
        }
        TestUtils.assertChiSquareAccept(expected, counts, 0.001);


        // Mean 5
        quartiles = TestUtils.getDistributionQuartiles(new ExponentialDistribution(5));
        counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextExponential(5);
            TestUtils.updateCounts(value, counts, quartiles);

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.