64 lines
1.8 KiB
Java
64 lines
1.8 KiB
Java
package statistics;
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// Gaussian CDF Taylor approximation
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// Code borrowed from http://www.cs.princeton.edu/introcs/21function/Gaussian.java.html 19/9 2006
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/*************************************************************************
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* Compilation: javac Gaussian.java
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* Execution: java Gaussian x mu sigma
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*
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* Function to compute the Gaussian pdf (probability density function)
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* and the Gaussian cdf (cumulative density function)
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*
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* % java Gaussian 820 1019 209
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* 0.17050966869132111
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*
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* % java Gaussian 1500 1019 209
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* 0.9893164837383883
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*
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* % java Gaussian 1500 1025 231
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* 0.9801220907365489
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*
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*************************************************************************/
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public class Gaussian {
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// return phi(x) = standard Gaussian pdf
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public static double phi(double x) {
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return Math.exp(-x*x / 2) / Math.sqrt(2 * Math.PI);
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}
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// return phi(x) = Gaussian pdf with mean mu and stddev sigma
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public static double phi(double x, double mu, double sigma) {
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return phi((x - mu) / sigma) / sigma;
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}
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// return Phi(z) = standard Gaussian cdf using Taylor approximation
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public static double Phi(double z) {
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if (z < -8.0) return 0.0;
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if (z > 8.0) return 1.0;
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double sum = 0.0, term = z;
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for (int i = 3; sum + term != sum; i += 2) {
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sum = sum + term;
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term = term * z * z / i;
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}
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return 0.5 + sum * phi(z);
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}
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// return Phi(z, mu, sigma) = Gaussian cdf with mean mu and stddev sigma
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public static double Phi(double z, double mu, double sigma) {
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return Phi((z - mu) / sigma);
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}
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public static void main(String[] args) {
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double z = Double.parseDouble(args[0]);
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double mu = Double.parseDouble(args[1]);
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double sigma = Double.parseDouble(args[2]);
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System.out.println(Phi(z, mu, sigma));
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}
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}
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