Examples of BinomialDistribution

@version $Revision: 920852 $ $Date: 2010-03-09 13:53:44 +0100 (mar. 09 mars 2010) $
  • org.apache.commons.math3.distribution.BinomialDistribution
    pedia.org/wiki/Binomial_distribution">Binomial distribution (Wikipedia) @see Binomial Distribution (MathWorld)
  • org.jamesii.core.math.random.distributions.BinomialDistribution
    The Class BinomialDistribution. WARNING! Might produce incorrect results with a high number of trials. @author Jan Himmelspach
  • org.jquantlib.math.distributions.BinomialDistribution
    pedia.org/wiki/Binomial_distribution">Binomial Distribution @author Richard Gomes @author Dominik Holenstein

    • Examples of org.apache.commons.math.distribution.BinomialDistribution

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    import uk.ac.cam.ch.wwmm.ptclib.xml.XOMTools;

    public class ReactCollocations {

      public static double binomialProbEqualGreater(int trials, int success, double prob) throws MathException {
        BinomialDistribution bd = new BinomialDistributionImpl(trials, prob);
        double score = 0;
        for(int i=success;i<=trials;i++) {
          score += bd.probability(i);
        }
        //double score = bd.cumulativeProbability(success-1);
        System.out.println("bd:\t" + trials + "\t" + success + "\t" + prob + "\t" + (1.0-score) + "\t" + bd.cumulativeProbability(success-1));
        return 1.0 - score;
      }
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    Examples of org.apache.commons.math.distribution.BinomialDistribution

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       * @param args
       */
      public static void main(String[] args) throws Exception {
        if(true) {
          long time = System.currentTimeMillis();
          BinomialDistribution bd = new BinomialDistributionImpl(10000000, 0.5);
          double d = bd.cumulativeProbability(3456789);
          //for(int i=-1;i<=100000;i++) {
          //  double d = bd.cumulativeProbability(i);
          //  //System.out.println(i + "\t" + bd.cumulativeProbability(i) + "\t" + (1.0 - bd.cumulativeProbability(i)));
          //}
          System.out.println(System.currentTimeMillis() - time);
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    Examples of org.apache.commons.math.distribution.BinomialDistribution

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        if(number>trails || number <0)
          throw new SSErrorXelException(SSError.NUM);
        else{
          DistributionFactory factory = DistributionFactory.newInstance();
          BinomialDistribution bd = factory.createBinomialDistribution(trails, p_s);
          if(isCumulative)
            return UtilFns.validateNumber(bd.cumulativeProbability(number));
          else
            return UtilFns.validateNumber(bd.probability(number));
        }
      }
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    Examples of org.apache.commons.math3.distribution.BinomialDistribution

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         * @param numberOfTrials number of trials of the Binomial distribution
         * @param probabilityOfSuccess probability of success of the Binomial distribution
         * @return random value sampled from the Binomial(numberOfTrials, probabilityOfSuccess) distribution
         */
        public int nextBinomial(int numberOfTrials, double probabilityOfSuccess) {
            return new BinomialDistribution(getRandomGenerator(), numberOfTrials, probabilityOfSuccess).sample();
        }
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    Examples of org.apache.commons.math3.distribution.BinomialDistribution

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            if (alternativeHypothesis == null) {
                throw new NullArgumentException();
            }

            // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
            final BinomialDistribution distribution = new BinomialDistribution(null, numberOfTrials, probability);
            switch (alternativeHypothesis) {
            case GREATER_THAN:
                return 1 - distribution.cumulativeProbability(numberOfSuccesses - 1);
            case LESS_THAN:
                return distribution.cumulativeProbability(numberOfSuccesses);
            case TWO_SIDED:
                int criticalValueLow = 0;
                int criticalValueHigh = numberOfTrials;
                double pTotal = 0;

                while (true) {
                    double pLow = distribution.probability(criticalValueLow);
                    double pHigh = distribution.probability(criticalValueHigh);

                    if (pLow == pHigh) {
                        pTotal += 2 * pLow;
                        criticalValueLow++;
                        criticalValueHigh--;
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    Examples of org.apache.commons.math3.distribution.BinomialDistribution

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            BinomialDistributionTest testInstance = new BinomialDistributionTest();
            int[] densityPoints = testInstance.makeDensityTestPoints();
            double[] densityValues = testInstance.makeDensityTestValues();
            int sampleSize = 1000;
            int length = TestUtils.eliminateZeroMassPoints(densityPoints, densityValues);
            BinomialDistribution distribution = (BinomialDistribution) testInstance.makeDistribution();
            double[] expectedCounts = new double[length];
            long[] observedCounts = new long[length];
            for (int i = 0; i < length; i++) {
                expectedCounts[i] = sampleSize * densityValues[i];
            }
            randomData.reSeed(1000);
            for (int i = 0; i < sampleSize; i++) {
              int value = randomData.nextBinomial(distribution.getNumberOfTrials(),
                      distribution.getProbabilityOfSuccess());
              for (int j = 0; j < length; j++) {
                  if (value == densityPoints[j]) {
                      observedCounts[j]++;
                  }
              }
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    Examples of org.apache.commons.math3.distribution.BinomialDistribution

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         * @param probabilityOfSuccess probability of success of the Binomial distribution
         * @return random value sampled from the Binomial(numberOfTrials, probabilityOfSuccess) distribution
         * @since 2.2
         */
        public int nextBinomial(int numberOfTrials, double probabilityOfSuccess) {
            return nextInversionDeviate(new BinomialDistribution(numberOfTrials, probabilityOfSuccess));
        }
    View Full Code Here

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

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         * @param numberOfTrials number of trials of the Binomial distribution
         * @param probabilityOfSuccess probability of success of the Binomial distribution
         * @return random value sampled from the Binomial(numberOfTrials, probabilityOfSuccess) distribution
         */
        public int nextBinomial(int numberOfTrials, double probabilityOfSuccess) {
            return new BinomialDistribution(getRandomGenerator(), numberOfTrials, probabilityOfSuccess).sample();
        }
    View Full Code Here

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

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            BinomialDistributionTest testInstance = new BinomialDistributionTest();
            int[] densityPoints = testInstance.makeDensityTestPoints();
            double[] densityValues = testInstance.makeDensityTestValues();
            int sampleSize = 1000;
            int length = TestUtils.eliminateZeroMassPoints(densityPoints, densityValues);
            BinomialDistribution distribution = (BinomialDistribution) testInstance.makeDistribution();
            double[] expectedCounts = new double[length];
            long[] observedCounts = new long[length];
            for (int i = 0; i < length; i++) {
                expectedCounts[i] = sampleSize * densityValues[i];
            }
            randomData.reSeed(1000);
            for (int i = 0; i < sampleSize; i++) {
              int value = randomData.nextBinomial(distribution.getNumberOfTrials(),
                      distribution.getProbabilityOfSuccess());
              for (int j = 0; j < length; j++) {
                  if (value == densityPoints[j]) {
                      observedCounts[j]++;
                  }
              }
    View Full Code Here

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

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            }
            if (alternativeHypothesis == null) {
                throw new NullArgumentException();
            }

            final BinomialDistribution distribution = new BinomialDistribution(numberOfTrials, probability);
            switch (alternativeHypothesis) {
            case GREATER_THAN:
                return 1 - distribution.cumulativeProbability(numberOfSuccesses - 1);
            case LESS_THAN:
                return distribution.cumulativeProbability(numberOfSuccesses);
            case TWO_SIDED:
                int criticalValueLow = 0;
                int criticalValueHigh = numberOfTrials;
                double pTotal = 0;

                while (true) {
                    double pLow = distribution.probability(criticalValueLow);
                    double pHigh = distribution.probability(criticalValueHigh);

                    if (pLow == pHigh) {
                        pTotal += 2 * pLow;
                        criticalValueLow++;
                        criticalValueHigh--;
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