Ideation Project DA Ruwe
This program provides us with an agent based simulation of an ideation game.
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ideation.NormalDistribution Class Reference

Implements the standard and non standard probability density function (pdf) and cumulative distribution function (cdf) for normal distributions. More...

List of all members.

Static Public Member Functions

static double pdf (double mean, double variance, double x)
 The probabability density function at point x of the normal distribution.
static double cdf1 (double x)
 Approximation of the standard cumulative density function of the normal distribution.
static double erf (double x)
 Approximation of the error function according to Winitzki.
static double cdf (double mean, double variance, double x)
 Approximation of the cumulative density function of the normal distribution.
static void main (String args[])
 test: Tests for Normal Distributions...

Static Public Attributes

static final double b0 = 0.2316419
 Parameter for Abramovitz Stegun Method.
static final double b1 = 0.319381530
 Parameter for Abramovitz Stegun Method.
static final double b2 = -0.356563782
 Parameter for Abramovitz Stegun Method.
static final double b3 = 1.781477937
 Parameter for Abramovitz Stegun Method.
static final double b4 = -1.821255978
 Parameter for Abramovitz Stegun Method.
static final double b5 = 1.330274429
 Parameter for Abramovitz Stegun Method.

Detailed Description

Accuracies:

Uses approximations by Abramovitz and Stegun http://www.math.sfu.ca/~cbm/aands/page_932.htm and Sergeij Winitzki http://www.scribd.com/doc/82414963/Winitzki-Approximation-to-Error-Function

Author:
Ruediger Ruwe <ruediger.ruwe @ rwth-aachen.de>
Version:
1.0
Since:
10.08.2012

Member Function Documentation

static double ideation.NormalDistribution.cdf ( double  mean,
double  variance,
double  x 
) [static]

Uses the approximations used by ideation.NormalDistribution#cdf1

Parameters:
meanmean
variancevariance (sigma)^2
xx
Returns:
cdf(x)
static double ideation.NormalDistribution.cdf1 ( double  x) [static]
Parameters:
x
Returns:
pdf(x)
static double ideation.NormalDistribution.erf ( double  x) [static]

The accuracy could be higher (about 5-6 significant figures) but there are no iterations needed which will provide a decent efficiency.

Parameters:
xx
Returns:
erf(x)
static void ideation.NormalDistribution.main ( String  args[]) [static]

Uses the approximations used by ideation.NormalDistribution#cdf1

For test purposes you can enter the package in this class and check the output with other calculations.

static double ideation.NormalDistribution.pdf ( double  mean,
double  variance,
double  x 
) [static]
Parameters:
meanmean
variancevariance (sigma^2)
xpoint of interest
Returns:
pdf(x)

The documentation for this class was generated from the following file:
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