Class NormalDistribution

java.lang.Object
pal.statistics.NormalDistribution

public class NormalDistribution extends Object
normal distribution (pdf, cdf, quantile)
Version:
$Id: NormalDistribution.java,v 1.3 2001/07/13 14:39:13 korbinian Exp $
Author:
Korbinian Strimmer
  • Constructor Summary

    Constructors
    Constructor
    Description
     
  • Method Summary

    Modifier and Type
    Method
    Description
    static double
    cdf(double x, double m, double sd)
    cumulative density function
    static double
    mean(double m, double sd)
    mean
    static double
    pdf(double x, double m, double sd)
    probability density function
    static double
    quantile(double z, double m, double sd)
    quantiles (=inverse cumulative density function)
    static double
    variance(double m, double sd)
    variance

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
  • Constructor Details

    • NormalDistribution

      public NormalDistribution()
  • Method Details

    • pdf

      public static double pdf(double x, double m, double sd)
      probability density function
      Parameters:
      x - argument
      m - mean
      sd - standard deviation
      Returns:
      pdf at x
    • cdf

      public static double cdf(double x, double m, double sd)
      cumulative density function
      Parameters:
      x - argument
      m - mean
      sd - standard deviation
      Returns:
      cdf at x
    • quantile

      public static double quantile(double z, double m, double sd)
      quantiles (=inverse cumulative density function)
      Parameters:
      z - argument
      m - mean
      sd - standard deviation
      Returns:
      icdf at z
    • mean

      public static double mean(double m, double sd)
      mean
      Parameters:
      m - mean
      sd - standard deviation
      Returns:
      mean
    • variance

      public static double variance(double m, double sd)
      variance
      Parameters:
      m - mean
      sd - standard deviation
      Returns:
      variance