finMath lib documentation
net.finmath.functions

## Class NormalDistribution

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

All Methods
Modifier and Type Method and 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 probablity (quantile).
Returns:
The argument of the cumulative distribution function being assigned to p.