Package com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random

Examples of com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random.Well19937c

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        Random rand = new SecureRandom();
        int[] seed = new int[624];
        for (int i = 0; i < seed.length; i++) {
          seed[i] = rand.nextInt();
        }
        prng = new Well19937c(seed); // non-secure & fast
      }
      validateArguments();
    }
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     * {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
     * @throws NotStrictlyPositiveException if {@code mean <= 0}.
     * @since 2.1
     */
    public ExponentialDistribution(double mean, double inverseCumAccuracy) {
        this(new Well19937c(), mean, inverseCumAccuracy);
    }
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     * @param upper Upper bound (inclusive) of this distribution.
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     */
    public UniformIntegerDistribution(int lower, int upper)
        throws NumberIsTooLargeException {
        this(new Well19937c(), lower, upper);
    }
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     * @throws NumberIsTooLargeException if {@code a >= b} or if {@code c > b}.
     * @throws NumberIsTooSmallException if {@code c < a}.
     */
    public TriangularDistribution(double a, double c, double b)
        throws NumberIsTooLargeException, NumberIsTooSmallException {
        this(new Well19937c(), a, c, b);
    }
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     * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
     * or {@code sampleSize > populationSize}.
     */
    public HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize)
    throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
        this(new Well19937c(), populationSize, numberOfSuccesses, sampleSize);
    }
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     * cumulative probability estimates (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
     * @throws NumberIsTooSmallException if {@code mu < 0.5}
     * @throws NotStrictlyPositiveException if {@code omega <= 0}
     */
    public NakagamiDistribution(double mu, double omega, double inverseAbsoluteAccuracy) {
        this(new Well19937c(), mu, omega, inverseAbsoluteAccuracy);
    }
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     * cumulative probability estimates (defaults to
     * {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
     * @since 2.1
     */
    public BetaDistribution(double alpha, double beta, double inverseCumAccuracy) {
        this(new Well19937c(), alpha, beta, inverseCumAccuracy);
    }
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     * @throws NotStrictlyPositiveException if {@code sd <= 0}.
     * @since 2.1
     */
    public NormalDistribution(double mean, double sd, double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
        this(new Well19937c(), mean, sd, inverseCumAccuracy);
    }
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     * @param exponent Exponent.
     * @exception NotStrictlyPositiveException if {@code numberOfElements <= 0}
     * or {@code exponent <= 0}.
     */
    public ZipfDistribution(final int numberOfElements, final double exponent) {
        this(new Well19937c(), numberOfElements, exponent);
    }
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     * @throws OutOfRangeException if the probability of success is not in the
     * range {@code [0, 1]}.
     */
    public PascalDistribution(int r, double p)
        throws NotStrictlyPositiveException, OutOfRangeException {
        this(new Well19937c(), r, p);
    }
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