Examples of BetaDistributionImpl

    return LNorm.dlnorm(x, meanlog, sdlog, logP);
  }


  @DataParallel @Internal
  public static double dbeta(@Recycle double x, @Recycle double shape1, @Recycle double shape2, boolean log) {
    return d(new BetaDistributionImpl(shape1, shape2), x, log);
  }

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

    return Beta.dnbeta(x, shape1, shape2, ncp, log);
  }


  @DataParallel @Internal
  public static double pbeta(@Recycle double q, @Recycle double shape1, @Recycle double shape2, boolean lowerTail, boolean logP) {
    return p(new BetaDistributionImpl(shape1, shape2), q, lowerTail, logP);
  }

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

    return Beta.pnbeta(q, shape1, shape2, ncp, lowerTail, logP);
  }


  @DataParallel @Internal
  public static double qbeta(@Recycle double p, @Recycle double shape1, @Recycle double shape2, boolean lowerTail, boolean logP) {
    return q(new BetaDistributionImpl(shape1, shape2), p, lowerTail, logP);
  }

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

     * @return random value sampled from the beta(alpha, beta) distribution
     * @throws MathException if an error occurs generating the random value
     * @since 2.2
     */
    public double nextBeta(double alpha, double beta) throws MathException {
        return nextInversionDeviate(new BetaDistributionImpl(alpha, beta));
    }

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

        for (int i = 0; i < 10; i++) {
            quantiles[i] = randomData.nextUniform(0, 1);
        }
        // Reseed again so the inversion generator gets the same sequence
        randomData.reSeed(100);
        BetaDistributionImpl betaDistribution = new BetaDistributionImpl(2, 4);
        /*
         *  Generate a sequence of deviates using inversion - the distribution function
         *  evaluated at the random value from the distribution should match the uniform
         *  random value used to generate it, which is stored in the quantiles[] array.
         */
        for (int i = 0; i < 10; i++) {
            double value = randomData.nextInversionDeviate(betaDistribution);
            assertEquals(betaDistribution.cumulativeProbability(value), quantiles[i], 10E-9);
        } 
    }

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

            assertEquals(betaDistribution.cumulativeProbability(value), quantiles[i], 10E-9);
        } 
    }
    
    public void testNextBeta() throws Exception {
        double[] quartiles = TestUtils.getDistributionQuartiles(new BetaDistributionImpl(2,5));
        long[] counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextBeta(2, 5);
            TestUtils.updateCounts(value, counts, quartiles);

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

      return sum / total;
    }


    public double getBetaRandom() {
      try {
        return new BetaDistributionImpl(1 + sum, 1 + total - sum).sample();
      } catch (final MathException e) {
        e.printStackTrace();
        return -1;
      }
    }

Examples of org.apache.commons.math.distribution.BetaDistributionImpl

    _a = a;
    _b = b;


    _x = x;


    BetaDistributionImpl betaDistribution = new BetaDistributionImpl(_a, _b);


    // FIXME : Fix this
    _recoveryRate = 0.0; //betaDistribution.inverseCumulativeProbability(_x);


    _recoveryRateType = RecoveryRateType.STOCHASTIC;

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