C# 클래스 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.

상속: IContinuousDistribution

파일 보기 프로젝트 열기: debop/NFramework 1 사용 예제들

공개 메소드들

메소드	설명
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

비공개 메소드들

메소드	설명
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

메소드 상세

CumulativeDistribution() 공개 메소드

확률 분포 계산을 위한 누적분포함수

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

Density() 공개 메소드

분포의 확률 밀도

public Density ( double x ) : double
x	double
리턴	double

Density() 공개 정적인 메소드

정규분포의 밀도를 계산합니다.

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

DensityLn() 공개 메소드

분포의 로그 확률 밀도

public DensityLn ( double x ) : double
x	double
리턴	double

DensityLn() 공개 정적인 메소드

정규분포의 로그 밀도를 계산합니다.

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

InverseCumulativeDistribution() 공개 메소드

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.
리턴	double

Normal() 공개 메소드

생성자

public Normal ( ) : System
리턴	System

Normal() 공개 메소드

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
리턴	System

Sample() 공개 메소드

분포의 무작위 값을 제공합니다.

public Sample ( ) : double
리턴	double

Sample() 공개 정적인 메소드

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.
리턴	double

Samples() 공개 메소드

현 분포의 무작위 값을 열거합니다.

public Samples ( ) : IEnumerable
리턴	IEnumerable

Samples() 공개 정적인 메소드

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.
리턴	IEnumerable

ToString() 공개 메소드

public ToString ( ) : string
리턴	string

WithMeanPrecision() 공개 정적인 메소드

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

WithMeanStDev() 공개 정적인 메소드

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

WithMeanVariance() 공개 정적인 메소드

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