Package cern.jet.random.engine

Examples of cern.jet.random.engine.MersenneTwister64

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public class QDigestTest {

    @Test
    public void testComprehensiveOnMixture() {
        RandomEngine r = new MersenneTwister64(0);
        Normal[] dists = new Normal[]{
                new Normal(100, 50, r),
                new Normal(150, 20, r),
                new Normal(500, 300, r),
                new Normal(10000, 10000, r),
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   * @param mu The location parameter
   * @param sigma The scale parameter, not negative or zero
   * @param ksi The shape parameter, not zero
   */
  public GeneralizedParetoDistribution(final double mu, final double sigma, final double ksi) {
    this(mu, sigma, ksi, new MersenneTwister64(new Date()));
  }
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  /**
   * @param degrees The degrees of freedom of the distribution, not less than one
   */
  public ChiSquareDistribution(final double degrees) {
    this(degrees, new MersenneTwister64(new Date()));
  }
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  /**
   * @param mean The mean of the distribution
   * @param standardDeviation The standard deviation of the distribution, not negative or zero
   */
  public NormalDistribution(final double mean, final double standardDeviation) {
    this(mean, standardDeviation, new MersenneTwister64(new Date()));
  }
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  /**
   * @param degFreedom The number of degrees of freedom, not negative or zero
   */
  public StudentTDistribution(final double degFreedom) {
    this(degFreedom, new MersenneTwister64(new Date()));
  }
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  /**
   * @param mu The location parameter
   * @param b The scale parameter, greater than zero
   */
  public LaplaceDistribution(final double mu, final double b) {
    this(mu, b, new MersenneTwister64(new Date()));
  }
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  }

  public SmileInterpolator(final int seed, final VolatilityFunctionProvider<T> model, final WeightingFunction weightFunction) {
    ArgumentChecker.notNull(model, "model");
    ArgumentChecker.notNull(weightFunction, "weightFunction");
    _random = new MersenneTwister64(seed);
    _model = model;
    _weightingFunction = weightFunction;
  }
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    _vol2 = vol2;
    _lambda12 = lambda12;
    _lambda21 = lambda21;
    _probState1 = probState1;
    _pi1 = lambda21 / (lambda12 + lambda21);
    _rand = new MersenneTwister64(seed);
  }
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   * @param seed The seed
   */
  public VarianceSwapPureMonteCarloCalculator(final int seed) {
    _useAntithetics = true;
    _calculateVariance = true;
    final RandomEngine random = new MersenneTwister64(seed);
    _norm = new NormalDistribution(0, 1.0, random);
  }
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   * @param calculateVariance true if the variance of the result is to be calculated
   */
  public VarianceSwapPureMonteCarloCalculator(final int seed, final boolean useAntithetics, final boolean calculateVariance) {
    _useAntithetics = useAntithetics;
    _calculateVariance = calculateVariance;
    final RandomEngine random = new MersenneTwister64(seed);
    _norm = new NormalDistribution(0, 1.0, random);
  }
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Related Classes of cern.jet.random.engine.MersenneTwister64

  • com.clearspring.analytics.stream.quantile.QDigestTest
  • com.opengamma.analytics.financial.equity.variance.pricing.EquityVarianceSwapMonteCarloCalculator
  • com.opengamma.analytics.financial.equity.variance.pricing.VarianceSwapPureMonteCarloCalculator
  • com.opengamma.analytics.financial.model.finitedifference.MarkovChain
  • com.opengamma.analytics.financial.model.volatility.smile.fitting.interpolation.SmileInterpolator
  • com.opengamma.analytics.math.interpolation.KrigingInterpolatorNDTest
  • com.opengamma.analytics.math.random.NormalRandomNumberGeneratorTest
  • com.opengamma.analytics.math.statistics.distribution.ChiSquareDistribution
  • com.opengamma.analytics.math.statistics.distribution.GeneralizedParetoDistribution
  • com.opengamma.analytics.math.statistics.distribution.LaplaceDistribution
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