Option2017Interface.DistFunctions.java Source code

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Here is the source code for Option2017Interface.DistFunctions.java

Source

package Option2017Interface;

/*
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import org.apache.commons.math3.distribution.NormalDistribution;

/**
 *
 * @author Paulino
 */
public class DistFunctions {
    /** Nuevas funciones usando la lib de Apache Commons
    * http://commons.apache.org/proper/commons-math/apidocs/index.html
        * @param z
        * @return 
    */
    public static double CNDF(double z) {

        NormalDistribution nD = new NormalDistribution();
        double cndf;

        cndf = nD.cumulativeProbability(z);
        return cndf;

    }// end CNDF segun Apache Common

    public static double PDF(double z) {

        NormalDistribution nD = new NormalDistribution();
        double pdf;
        pdf = nD.density(z);
        return pdf;

    }//end PDF segun Apache Common    

    // funciones de gauss

    // return phi(x) = standard Gaussian pdf
    public static double phi(double x) {
        return Math.exp(-x * x / 2) / Math.sqrt(2 * Math.PI);
    }

    // return phi(x, mu, signma) = Gaussian pdf with mean mu and stddev sigma
    public static double phi(double x, double mu, double sigma) {
        return phi((x - mu) / sigma) / sigma;
    }

    // return Phi(z) = standard Gaussian cdf using Taylor approximation
    public static double Phi(double z) {
        if (z < -8.0)
            return 0.0;
        if (z > 8.0)
            return 1.0;
        double sum = 0.0, term = z;
        for (int i = 3; sum + term != sum; i += 2) {
            sum = sum + term;
            term = term * z * z / i;
        }
        return 0.5 + sum * phi(z);
    }

    // return Phi(z, mu, sigma) = Gaussian cdf with mean mu and stddev sigma
    public static double Phi(double z, double mu, double sigma) {
        return Phi((z - mu) / sigma);
    }

    // Compute z such that Phi(z) = y via bisection search
    public static double PhiInverse(double y) {
        return PhiInverse(y, .00000001, -8, 8);
    }

    // bisection search
    private static double PhiInverse(double y, double delta, double lo, double hi) {
        double mid = lo + (hi - lo) / 2;
        if (hi - lo < delta)
            return mid;
        if (Phi(mid) > y)
            return PhiInverse(y, delta, lo, mid);
        else
            return PhiInverse(y, delta, mid, hi);
    }

    // returns the cumulative normal distribution function (CNDF)
    // for a standard normal: N(0,1)
    public static double CNDF2(double x) {
        int neg = (x < 0d) ? 1 : 0;
        if (neg == 1)
            x *= -1d;

        double k = (1d / (1d + 0.2316419 * x));
        double y = ((((1.330274429 * k - 1.821255978) * k + 1.781477937) * k - 0.356563782) * k + 0.319381530) * k;
        y = 1.0 - 0.398942280401 * Math.exp(-0.5 * x * x) * y;

        return (1d - neg) * y + neg * (1d - y);
    }

}