net.finmath.functions

Class NormalDistribution

java.lang.Object

net.finmath.functions.NormalDistribution

public class NormalDistribution
extends Object

Version:

1.0

Author:

Christian Fries

Method Summary

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.