package com.imsl.test.example.stat;

import com.imsl.stat.*;

/**
 * <p>
 * Generates a pseudorandom sample from a normal distribution and performs a
 * goodness of fit test.
 * </p>
 *
 * In this example, a normal random sample of size 1000 is generated via
 * <code>Random.nextGaussian</code>. <code>Random.setSeed</code> is first used
 * to set the seed. After the <code>ChiSquaredTest</code> constructor is called,
 * the random observations are added to the test one at a time to simulate
 * streaming data. The Chi-squared test is performed using
 * <code>Cdf.normal</code> as the cumulative distribution function object to see
 * how well the random numbers fit the normal distribution.
 *
 *
 * @see <a href="RandomEx1.java">Code</a>
 * @see <a href="doc-files/RandomEx1.out">Output</a>
 */
public class RandomEx1 implements CdfFunction {

    @Override
    public double cdf(double x) {
        return Cdf.normal(x);
    }

    public static void main(String args[]) throws Exception {
        int nObservations = 1000;
        Random r = new Random(123457L);
        ChiSquaredTest test = new ChiSquaredTest(new RandomEx1(), 10, 0);
        for (int k = 0; k < nObservations; k++) {
            test.update(r.nextNormal(), 1.0);
        }

        double p = test.getP();
        System.out.println("The P-value is " + p);
    }
}