Example usage for org.apache.commons.math3.distribution GammaDistribution cumulativeProbability

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution GammaDistribution cumulativeProbability.

Prototype

public double cumulativeProbability(double x) 

Source Link

Document

The implementation of this method is based on: <ul> <li> <a href="http://mathworld.wolfram.com/Chi-SquaredDistribution.html"> Chi-Squared Distribution</a>, equation (9).

Usage

From source file:com.mapr.synth.samplers.RandomWalkSamplerTest.java

@Test
public void testBasics() throws IOException {
    // this sampler has four variables
    // g1 is gamma distributed with alpha = 0.2, beta = 0.2
    // v1 is unit normal
    // v2 is normal with mean = 0, sd = 2
    // v3 is gamma-normal with dof=2, mean = 0.
    SchemaSampler s = new SchemaSampler(
            Resources.asCharSource(Resources.getResource("schema015.json"), Charsets.UTF_8).read());

    TDigest tdG1 = new AVLTreeDigest(500);
    TDigest tdG2 = new AVLTreeDigest(500);
    TDigest td1 = new AVLTreeDigest(500);
    TDigest td2 = new AVLTreeDigest(500);
    TDigest td3 = new AVLTreeDigest(500);

    double x1 = 0;
    double x2 = 0;
    double x3 = 0;

    for (int i = 0; i < 1000000; i++) {
        JsonNode r = s.sample();/*from   w  w  w  . j a  va2  s .co  m*/
        tdG1.add(r.get("g1").asDouble());
        tdG2.add(r.get("g2").asDouble());

        double step1 = r.get("v1").get("step").asDouble();
        td1.add(step1);
        x1 += step1;
        assertEquals(x1, r.get("v1").get("value").asDouble(), 0);
        assertEquals(x1, r.get("v1-bare").asDouble(), 0);

        double step2 = r.get("v2").get("step").asDouble();
        td2.add(step2);
        x2 += step2;
        assertEquals(x2, r.get("v2").get("value").asDouble(), 0);

        double step3 = r.get("v3").get("step").asDouble();
        td3.add(step3);
        x3 += step3;
        assertEquals(x3, r.get("v3").get("value").asDouble(), 0);
    }

    // now compare against reference distributions to test accuracy of the observed step distributions
    NormalDistribution normalDistribution = new NormalDistribution();
    GammaDistribution gd1 = new GammaDistribution(0.2, 5);
    GammaDistribution gd2 = new GammaDistribution(1, 1);
    TDistribution tDistribution = new TDistribution(2);
    for (double q : new double[] { 0.001, 0.01, 0.1, 0.2, 0.5, 0.8, 0.9, 0.99, 0.99 }) {
        double uG1 = gd1.cumulativeProbability(tdG1.quantile(q));
        assertEquals(q, uG1, (1 - q) * q * 10e-2);

        double uG2 = gd2.cumulativeProbability(tdG2.quantile(q));
        assertEquals(q, uG2, (1 - q) * q * 10e-2);

        double u1 = normalDistribution.cumulativeProbability(td1.quantile(q));
        assertEquals(q, u1, (1 - q) * q * 10e-2);

        double u2 = normalDistribution.cumulativeProbability(td2.quantile(q) / 2);
        assertEquals(q, u2, (1 - q) * q * 10e-2);

        double u3 = tDistribution.cumulativeProbability(td3.quantile(q));
        assertEquals(q, u3, (1 - q) * q * 10e-2);
    }
}

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