package com.imsl.test.example.stat.distributions;

import com.imsl.math.PrintMatrix;
import com.imsl.math.PrintMatrixFormat;
import com.imsl.stat.distributions.LogisticPD;
import java.text.DecimalFormat;

/**
 * <p>
 * Evaluates the logistic probability distribution.</p>
 * <p>
 * This example evaluates the logistic density, gradient, and hessian for a
 * small sample of data.</p>
 *
 * @see <a href="LogisticPDEx1.java">Code</a>
 * @see <a href="doc-files/LogisticPDEx1.out">Output</a>
 */
public class LogisticPDEx1 {

    public static void main(String[] args) {

        double[] x = {
            11.707046582345296,2.9154448753588817,7.374648574841656,
            5.558291914606187,8.38921517862132,-1.1445036313647128,
            13.688322228418551,5.822189639995519,9.315168188063211,
            4.028151081671112};
        
        LogisticPD lpd = new LogisticPD();

        double[] values = new double[x.length];
        for (int i = 0; i < x.length; i++) {
            values[i] = lpd.pdf(x[i], 5.0, 2.0);
        }

        PrintMatrixFormat pmf = new PrintMatrixFormat();
        pmf.setNumberFormat(new DecimalFormat("0.00000000"));

        PrintMatrix pm = new PrintMatrix("logistic(5.0,2.0) pdf values at x=");
        pm.print(pmf, x);

        pm.setTitle("f(x;5.0,2.0)=");
        pm.print(pmf, values);

        double[] gradient = lpd.getPDFGradientApproximation(x[0], 5.0, 2.0);
        
        String title=String.format("Gradient of f(x;5.0,2.0) at x= %1.8f",x[0]);
        pm.setTitle(title);
        pm.print(pmf, gradient);

        double[][] hessian = lpd.getPDFHessianApproximation(x[0], 5.0, 2.0);
        
        title=String.format("Hessian of f(x;5.0,2.0) at x= %1.8f",x[0]);
        pm.setTitle(title);
        pm.print(pmf, hessian);
    }
}