package com.imsl.test.example.stat;

import com.imsl.stat.*;
import com.imsl.math.*;

/**
 * <p>
 * Generates a pseudorandom sample from a discrete uniform distribution.
 * </p>
 *
 * <p>
 * In this example, <code>nextDiscrete</code> and
 * <code>nextUniformDiscrete</code> are each used to generate discrete uniform
 * pseudorandom numbers. Note that the probabilities across the possible values
 * must be equal, in order to generate uniformly from <code>nextDiscrete</code>.
 * Also note that since the same random seed is used, the methods produce the
 * same results.</p>
 *
 * $$\begin{array}{c}\operatorname{Pr}(X=1)=0.20\\
 * \operatorname{Pr}(X=2)=0.20\\\operatorname{Pr}(X=3)=0.20 \\
 * \operatorname{Pr}(X=4)=0.20\\\operatorname{Pr}(X=5)=0.20\end{array}$$
 *
 *
 *
 * @see <a href="RandomEx4.java">Code</a>
 * @see <a href="doc-files/RandomEx4.out">Output</a>
 */

public class RandomEx4 {

    static Random IMSLRandom() {
        Random r = new Random();
        r.setSeed(123457);
        r.setMultiplier(16807);
        return r;
    }

    public static void main(String args[]) {
        int[] deviates = new int[5];
        int[] deviatesUniform = new int[5];
        double[] prob1 = {.20, .20, .20, .20, .20};
        PrintMatrix pm = new PrintMatrix("Random deviates");
        PrintMatrixFormat pmf = new PrintMatrixFormat();
        Random r = IMSLRandom();

        for (int i = 0; i < 5; i++) {
            deviates[i] = r.nextDiscrete(1, prob1);
        }

        pmf.setNoColumnLabels();
        pmf.setNoRowLabels();
        pm.print(pmf, deviates);

        Random rUniform = IMSLRandom();

        for (int i = 0; i < 5; i++) {
            deviatesUniform[i] = rUniform.nextUniformDiscrete(5);
        }

        pm.print(pmf, deviatesUniform);
    }
}