C# Class NSoft.NFramework.Numerics.Distributions.Continuous.Normal

정규 분포. Implements the univariate Normal (or Gaussian) distribution. For details about this distribution, see Wikipedia - Normal distribution.

The distribution will use the System.Random by default. Users can get/set the random number generator by using the RandomSource property.

The statistics classes will check all the incoming parameters whether they are in the allowed range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters to false, all parameter checks can be turned off.

Inheritance: IContinuousDistribution

Mostra file Open project: debop/NFramework Class Usage Examples

Public Methods

Method	Description
CumulativeDistribution ( double x ) : double	확률 분포 계산을 위한 누적분포함수
Density ( double x ) : double	분포의 확률 밀도
Density ( double mean, double stDev, double x ) : double	정규분포의 밀도를 계산합니다.
DensityLn ( double x ) : double	분포의 로그 확률 밀도
DensityLn ( double mean, double stDev, double x ) : double	정규분포의 로그 밀도를 계산합니다.
InverseCumulativeDistribution ( double p ) : double	Computes the inverse cumulative distribution function of the normal distribution.
Normal ( ) : System	생성자
Normal ( double mean = 0.0, double stDev = 1.0, Func randomFactory = null ) : System	정규분포 생성자
Sample ( ) : double	분포의 무작위 값을 제공합니다.
Sample ( Random rnd, double mean, double stDev ) : double	Generates a sample from the normal distribution using the Box-Muller algorithm.
Samples ( ) : IEnumerable	현 분포의 무작위 값을 열거합니다.
Samples ( Random rnd, double mean, double stDev ) : IEnumerable	Generates a sequence of samples from the normal distribution using the Box-Muller algorithm.
ToString ( ) : string
WithMeanPrecision ( double mean, double precision ) : Normal
WithMeanStDev ( double mean, double stDev ) : Normal
WithMeanVariance ( double mean, double variance ) : Normal

Private Methods

Method	Description
AssertParameters ( double mean, double stddev ) : void
CumulativeDistribution ( double mean, double sdev, double x ) : double	Computes the cumulative distribution function of the normal distribution.
SampleBoxMuller ( Random rnd ) : double>.Tuple	Samples a pair of standard normal distributed random variables using the Box-Muller algorithm.
SetParameters ( double mean, double stdDev ) : void

Method Details

CumulativeDistribution() public method

확률 분포 계산을 위한 누적분포함수

public CumulativeDistribution ( double x ) : double
x	double	The location at which to compute the cumulative distribution function.
return	double

Density() public method

분포의 확률 밀도

public Density ( double x ) : double
x	double
return	double

Density() public static method

정규분포의 밀도를 계산합니다.

public static Density ( double mean, double stDev, double x ) : double
mean	double
stDev	double
x	double
return	double

DensityLn() public method

분포의 로그 확률 밀도

public DensityLn ( double x ) : double
x	double
return	double

DensityLn() public static method

정규분포의 로그 밀도를 계산합니다.

public static DensityLn ( double mean, double stDev, double x ) : double
mean	double
stDev	double
x	double
return	double

InverseCumulativeDistribution() public method

Computes the inverse cumulative distribution function of the normal distribution.

public InverseCumulativeDistribution ( double p ) : double
p	double	The location at which to compute the inverse cumulative density.
return	double

Normal() public method

생성자

public Normal ( ) : System
return	System

Normal() public method

정규분포 생성자

public Normal ( double mean = 0.0, double stDev = 1.0, Func randomFactory = null ) : System
mean	double	평균
stDev	double	표준편차
randomFactory	Func	난수발생기 Factory
return	System

Sample() public method

분포의 무작위 값을 제공합니다.

public Sample ( ) : double
return	double

Sample() public static method

Generates a sample from the normal distribution using the Box-Muller algorithm.

public static Sample ( Random rnd, double mean, double stDev ) : double
rnd	System.Random	The random number generator to use.
mean	double	The mean of the normal distribution from which to generate samples.
stDev	double	The standard deviation of the normal distribution from which to generate samples.
return	double

Samples() public method

현 분포의 무작위 값을 열거합니다.

public Samples ( ) : IEnumerable
return	IEnumerable

Samples() public static method

Generates a sequence of samples from the normal distribution using the Box-Muller algorithm.

public static Samples ( Random rnd, double mean, double stDev ) : IEnumerable
rnd	System.Random	The random number generator to use.
mean	double	The mean of the normal distribution from which to generate samples.
stDev	double	The standard deviation of the normal distribution from which to generate samples.
return	IEnumerable

ToString() public method

public ToString ( ) : string
return	string

WithMeanPrecision() public static method

public static WithMeanPrecision ( double mean, double precision ) : Normal
mean	double
precision	double
return	Normal

WithMeanStDev() public static method

public static WithMeanStDev ( double mean, double stDev ) : Normal
mean	double
stDev	double
return	Normal

WithMeanVariance() public static method

public static WithMeanVariance ( double mean, double variance ) : Normal
mean	double
variance	double
return	Normal