net.finmath.functions
Class NormalDistribution

java.lang.Object
  net.finmath.functions.NormalDistribution

public class NormalDistribution
extends Object

Author:

Christian Fries

Constructor Summary

NormalDistribution()

Method Summary

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	inverseCumulativeNormalDistribution_Wichura(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

Constructor Detail

NormalDistribution

public NormalDistribution()

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

inverseCumulativeNormalDistribution_Wichura

public static double inverseCumulativeNormalDistribution_Wichura(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.