Examples of BetaDistribution

com.mapr.stats.random.BetaDistribution
Sample from a beta distribution. The beta distribution has PDF of \[ p(x \mid \alpha, \alpha) = {\frac {\Gamma(\alpha+\beta)} {\Gamma(\alpha) \Gamma(\beta}} x^{\alpha-1} (1-x)^{\beta-1} \] Note that \( \frac {\Gamma(\alpha) \Gamma(\beta)} {\Gamma(\alpha+\beta)} \) and is known as the beta function \(B(\alpha, \beta)\). Sampling from the beta distribution \(x \sim B(\alpha, \beta)\) can be done by using the following procedure which depends on sampling from the gamma distribution \[ u \sim \Gamma(\alpha, 1) \\ v \sim \Gamma(\beta, 1) \\ x = \frac u {u+v} \]
org.apache.commons.math3.distribution.BetaDistribution
pedia.org/wiki/Beta_distribution">Beta distribution @since 2.0 (changed to concrete class in 3.0)

Examples of com.mapr.stats.random.BetaDistribution


    private double x;
    private double pdf = 0;


    public BetaWalk(double alpha, double beta, double stepSize) {
        this.bd = new BetaDistribution(alpha, beta, rand);
        this.stepSize = stepSize;
        x = bd.nextDouble();
        if (x < 0) {
            System.out.printf("heh?\n");
        }

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Examples of com.mapr.stats.random.BetaDistribution

        this.featureMap = featureMap;
        m = featureMap.numCols();
        this.state = new DenseMatrix(m, 2);
        this.state.viewColumn(0).assign(alpha_0);
        this.state.viewColumn(1).assign(beta_0);
        this.rand = new BetaDistribution(1, 1);
    }

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

     * @param alpha first distribution shape parameter
     * @param beta second distribution shape parameter
     * @return random value sampled from the beta(alpha, beta) distribution
     */
    public double nextBeta(double alpha, double beta) {
        return new BetaDistribution(getRandomGenerator(), alpha, beta,
                BetaDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }

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

        for (int i = 0; i < 10; i++) {
            quantiles[i] = rdg.nextUniform(0, 1);
        }
        // Reseed again so the inversion generator gets the same sequence
        rg.setSeed(100);
        BetaDistribution betaDistribution = new BetaDistribution(rg, 2, 4,
                                                                 BetaDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        /*
         *  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 = betaDistribution.sample();
            Assert.assertEquals(betaDistribution.cumulativeProbability(value), quantiles[i], 10E-9);
        }
    }

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

        }
    }


    @Test
    public void testNextBeta() {
        double[] quartiles = TestUtils.getDistributionQuartiles(new BetaDistribution(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);

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

     * @param beta second distribution shape parameter
     * @return random value sampled from the beta(alpha, beta) distribution
     * @since 2.2
     */
    public double nextBeta(double alpha, double beta) {
        return nextInversionDeviate(new BetaDistribution(alpha, beta));
    }

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

     * @param alpha first distribution shape parameter
     * @param beta second distribution shape parameter
     * @return random value sampled from the beta(alpha, beta) distribution
     */
    public double nextBeta(double alpha, double beta) {
        return new BetaDistribution(getRandomGenerator(), alpha, beta,
                BetaDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }

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

        for (int i = 0; i < 10; i++) {
            quantiles[i] = rdg.nextUniform(0, 1);
        }
        // Reseed again so the inversion generator gets the same sequence
        rg.setSeed(100);
        BetaDistribution betaDistribution = new BetaDistribution(rg, 2, 4,
                                                                 BetaDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        /*
         *  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 = betaDistribution.sample();
            Assert.assertEquals(betaDistribution.cumulativeProbability(value), quantiles[i], 10E-9);
        }
    }

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

        }
    }


    @Test
    public void testNextBeta() {
        double[] quartiles = TestUtils.getDistributionQuartiles(new BetaDistribution(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);

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

            container.add(comp, c);


            c.gridx++;
            comp = createComponent("Beta", 0, 1,
                                   new String[] { "α=β=0.5", "α=5,β=1", "α=1,β=3", "α=2,β=2", "α=2,β=5" },
                                   new BetaDistribution(0.5, 0.5),
                                   new BetaDistribution(5, 1),
                                   new BetaDistribution(1, 3),
                                   new BetaDistribution(2, 2),
                                   new BetaDistribution(2, 5));
            container.add(comp, c);


            c.gridx++;
            comp = createComponent("Cauchy", -5, 5,
                                   new String[] { "x=0,γ=0.5", "x=0,γ=1", "x=0,γ=2", "x=-2,γ=1" },

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