Examples of GaussianDistribution

be.ac.ulg.montefiore.run.distributions.GaussianDistribution
This class implements a Gaussian distribution.
de.mh4j.util.GaussianDistribution
org.dmg.pmml.pmml_4_2.descr.GaussianDistribution
3.org/2001/XMLSchema}anyType"> <sequence> <element ref="{http://www.dmg.org/PMML-4_2}Extension" maxOccurs="unbounded" minOccurs="0"/> </sequence> <attribute name="mean" use="required" type="{http://www.dmg.org/PMML-4_2}REAL-NUMBER" /> <attribute name="variance" use="required" type="{http://www.dmg.org/PMML-4_2}REAL-NUMBER" /> </restriction> </complexContent> </complexType>

Examples of be.ac.ulg.montefiore.run.distributions.GaussianDistribution

     * Proportions : 1/3, 2/3
     */
    ObservationReal[] observations = new ObservationReal[nbObservations];
    
    for (int g = 0, i = 0; g < 2; g++) {
      RandomDistribution d = new GaussianDistribution(g * 4.,
          1 + g);
      
      for (; i < ((g == 0) ? nbObservations / 3 : nbObservations); i++)
        observations[i] = new ObservationReal(d.generate());
    }
    
    // Fit distribution to observations
    OpdfGaussianMixture gm = new OpdfGaussianMixture(2);

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Examples of be.ac.ulg.montefiore.run.distributions.GaussianDistribution

   * Builds a new gaussian probability distribution with zero mean and
   * unit variance.
   */
  public OpdfGaussian()
  {
    distribution = new GaussianDistribution();
  }

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Examples of be.ac.ulg.montefiore.run.distributions.GaussianDistribution

   * @param mean The distribution's mean.
   * @param variance The distribution's variance.
   */
  public OpdfGaussian(double mean, double variance)
  {
    distribution = new GaussianDistribution(mean, variance);
  }

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Examples of be.ac.ulg.montefiore.run.distributions.GaussianDistribution

      double d = o.value - mean;
      
      variance += d * d * weights[i++];
    }
    
    distribution = new GaussianDistribution(mean, variance);
  }

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Examples of de.mh4j.util.GaussianDistribution

        this.matingSelector = matingSelector;
        this.recombinator = recombinator;
        this.mutator = mutator;
        this.darwin = darwin;


        random = new GaussianDistribution();
        mutator.setRandom(random);
    }

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Examples of org.dmg.pmml.pmml_4_2.descr.GaussianDistribution

        return resolveAggregationStrategy( strat ).getAggregator();
    }


    public String extractDistributionParameters( Object d ) {
        if ( d instanceof GaussianDistribution ) {
            GaussianDistribution gd = (GaussianDistribution) d;
            return "new Double[] { " + gd.getMean() + ", " + gd.getVariance() + " }";
        } else if ( d instanceof PoissonDistribution ) {
            PoissonDistribution pd = (PoissonDistribution) d;
            return "new Double[] { " + pd.getMean() + " }";
        } else if ( d instanceof UniformDistribution ) {
            UniformDistribution ud = (UniformDistribution) d;

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