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

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

/**
 * <p>
 * Evaluates the log normal probability distribution.</p>
 * <p>
 * This example evaluates the log normal density, gradient, and hessian for a
 * small sample of data.</p>
 *
 * @see <a href="LogNormalPDEx1.java">Code</a>
 * @see <a href="doc-files/LogNormalPDEx1.out">Output</a>
 */

public class LogNormalPDEx1 {

    public static void main(String[] args) {

        double[] x = {46.657860153788675, 13.11758795134333, 5.745848033140661,
            11.938973204787175, 0.7861595073630269, 7.573448549416857,
            37.58546296416137, 2.945815957716158, 5.80958651458377,
            15.017807093913715};

        LogNormalPD lnpd = new LogNormalPD();

        double[] values = new double[x.length];
        for (int i = 0; i < x.length; i++) {
            values[i] = lnpd.pdf(x[i], 2.0, 1.0);
        }
        PrintMatrixFormat pmf = new PrintMatrixFormat();
        pmf.setNumberFormat(new DecimalFormat("0.00000000"));

        PrintMatrix pm = new PrintMatrix("LogNormal(2.0,1.0) pdf values at x=");
        pm.print(pmf, x);

        pm.setTitle("f(x;2.0,1.0)=");
        pm.print(pmf, values);

        double[] gradient = lnpd.getPDFGradientApproximation(x[0], 2.0, 1.0);
        
        String title=String.format("Gradient of f(x;2.0,1.0) at x= %1.8f",x[0]);
        pm.setTitle(title);
        pm.print(pmf, gradient);

        double[][] hessian = lnpd.getPDFHessianApproximation(x[0], 2.0, 1.0);
        
        title=String.format("Hessian of f(x;2.0,1.0) at x= %1.8f",x[0]);
        pm.setTitle(title);
        pm.print(pmf, hessian);
    }
}