Examples of BinomialDistribution

    @Test
    public void testErrorBound()
            throws Exception
    {
        int trials = 20;
        BinomialDistribution binomial = new BinomialDistribution(trials, 0.5);


        int successes = 0;
        Random rand = new Random(0);
        for (int i = 0; i < trials; i++) {
            int sum = 1_000;
            List<TupleInfo> tupleInfos = ImmutableList.of(TupleInfo.SINGLE_LONG, TupleInfo.SINGLE_LONG);
            PageBuilder builder = new PageBuilder(tupleInfos);
            for (int j = 0; j < sum; j++) {
                if (rand.nextDouble() < 0.5) {
                    builder.getBlockBuilder(0).append(1);
                    builder.getBlockBuilder(1).append(2);
                }
            }


            AggregationFunction function = new DeterministicBootstrappedAggregation(LONG_SUM);


            successes += approximateAggregationWithinErrorBound(function, 1, 0.5, (double) sum, builder.build()) ? 1 : 0;
        }


        // Since we used a confidence of 0.5, successes should have a binomial distribution B(n=20, p=0.5)
        assertTrue(binomial.inverseCumulativeProbability(0.01) < successes && successes < binomial.inverseCumulativeProbability(0.99));
    }

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

                int m = idPWM.getColumnSum(j);
                int c_xj = idPWM.getMatrix()[i][j]; // count of residue at position j
                double p_xj = ((double) bGPWM.getMatrix()[i][j])/((double) bGPWM.getColumnSum(j));
                double bin_prob = 0.00;
                for(int trial = c_xj; trial <= m; trial++){
                    BinomialDistribution bnDistr = new BinomialDistribution(trial,p_xj);
                    bin_prob = bin_prob + bnDistr.probability(trial);
                    //int printbin = (m - c_xj)/20;
                    if(trial%10==0){
                        System.out.println("\t\t\tBinomial probability of "+ aminoA_symbols[i] + ", " + 
                                relative_positions[j] + " at iteration " + trial + " of " + m + " is " + 
                                   bin_prob);

Examples of org.jamesii.core.math.random.distributions.BinomialDistribution

   * @param maxSize
   *          the max size
   */
  @Override
  public void mutate(double mutationRate, int minSize, int maxSize) {
    BinomialDistribution mutationNumberDistribution =
        new BinomialDistribution(getRNG(), mutationRate, length);
    int numOfMutations =
        (int) Math.round(mutationNumberDistribution.getRandomNumber());
    if (numOfMutations > genome.size()) {
      numOfMutations = genome.size();
    }
    int[] mutationPositions =
        RandomSampler.sampleUnique(numOfMutations, genome.size(), getRNG());

Examples of org.jamesii.core.math.random.distributions.BinomialDistribution

   *          the probability of an mutation
   * 
   */
  @Override
  public void mutate(double mutationRate, int minSize, int maxSize) {
    BinomialDistribution mutationNumberDistribution =
        new BinomialDistribution(getRNG(), mutationRate, genome.length);
    int numOfMutations =
        (int) Math.round(mutationNumberDistribution.getRandomNumber());
    int[] mutationPositions =
        RandomSampler.sampleUnique(numOfMutations, genome.length, getRNG());
    for (int mutationPosition : mutationPositions) {
      genome[mutationPosition] = !genome[mutationPosition];
    }

Examples of org.jamesii.core.math.random.distributions.BinomialDistribution

  /** Applies test to normally distributed and binomially distributed samples. */
  public void testNormalVsBinomialSample() {
    List<Double> normalDistSample =
        getRandomSample(new NormalDistribution(random, 5.0, 2.0));
    List<Double> binomialDistSample =
        getRandomSample(new BinomialDistribution(random));
    checkTestResult(normalDistSample, binomialDistSample);
  }

Examples of org.jquantlib.math.distributions.BinomialDistribution

        };


        final double p = 0.5;        // p = probability
        final int n = testvalues.length; // n = number of trials


        final BinomialDistribution binomdist = new BinomialDistribution(p,n);


        for(int i=0;i<n;i++){
            final int z = i;
            final double expected = testvalues[i];
            final double computed = binomdist.op(z);


            // double tolerance = (z<6 ) ? 1.0e-15: 1.0e-10;
            final double tolerance = 1.0e-15; // try to to get 1.0e-15 accuracy whenever possible


            //assertEquals(expected, computed, tolerance);

Examples of org.jquantlib.math.distributions.BinomialDistribution

         return pn.get(n);
     }




     public static double  evaluateBinomialDistributionValue(double probability, int k) {
         BinomialDistribution bs  = new BinomialDistribution(probability, 0);
         return bs.op(k);


     }