Example 1: Random Number Generation

In this example, a discrete normal random sample of size 1000 is generated via Random.nextGaussian . Random.setSeed is first used to set the seed. After the ChiSquaredTest 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 Cdf.normal as the cumulative distribution function object to see how well the random numbers fit the normal distribution.

import com.imsl.stat.*;

public class RandomEx1 implements CdfFunction {

    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);


The P-value is 0.5518855965158241
Link to Java source.