## Class NormalDistribution

• public class NormalDistribution
extends Object
Version:
1.0
Author:
Christian Fries
• ### Method Summary

All Methods
Modifier and Type Method Description
static double cumulativeDistribution​(double x)
Cumulative distribution function of the standard normal distribution.
static double density​(double x)
Returns the value of the density at x.
static double inverseCumulativeDistribution​(double p)
Inverse of the cumulative distribution function of the standard normal distribution using Jakarta commons-math
static double inverseCumulativeNormalDistributionWichura​(double p)
Inverse of the cumulative distribution function of the standard normal distribution Java Version of Michael J.
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Method Detail

• #### density

public static double density​(double x)
Returns the value of the density at x.
Parameters:
x - Argument
Returns:
The value of the density at x.
• #### cumulativeDistribution

public static double cumulativeDistribution​(double x)
Cumulative distribution function of the standard normal distribution. The implementation is currently using Jakarta commons-math
Parameters:
x - A sample point
Returns:
The probability of being below x, given x is standard normal
• #### inverseCumulativeDistribution

public static double inverseCumulativeDistribution​(double p)
Inverse of the cumulative distribution function of the standard normal distribution using Jakarta commons-math
Parameters:
p - The probability
Returns:
The quantile
• #### inverseCumulativeNormalDistributionWichura

public static double inverseCumulativeNormalDistributionWichura​(double p)
Inverse of the cumulative distribution function of the standard normal distribution Java Version of Michael J. Wichura: Algorithm AS241 Appl. Statist. (1988) Vol. 37, No. 3 Produces the normal deviate z corresponding to a given lower tail area of p; z is accurate to about 1 part in 10**16. The hash sums below are the sums of the mantissas of the coefficients. they are included for use in checking transcription.
Parameters:
p - The probability (quantile).
Returns:
The argument of the cumulative distribution function being assigned to p.