C# 클래스 Accord.Statistics.Distributions.Univariate.NormalDistribution

상속: UnivariateContinuousDistribution
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공개 메소드들

메소드 설명
Clone ( ) : object

Creates a new object that is a copy of the current instance.

DistributionFunction ( double x ) : double

Gets the cumulative distribution function (cdf) for the this distribution evaluated at point x.

The Cumulative Distribution Function (CDF) describes the cumulative probability that a given value or any value smaller than it will occur.

The calculation is computed through the relationship to the function as erfc(-z/sqrt(2)) / 2.

References: http://mathworld.wolfram.com/NormalDistributionFunction.html

Fit ( double observations, double weights ) : IDistribution

Fits the underlying distribution to a given set of observations.

NormalDistribution ( ) : System

Constructs a Gaussian distribution with zero mean and unit variance.

NormalDistribution ( double mean ) : System

Constructs a Gaussian distribution with given mean and unit variance.

NormalDistribution ( double mean, double variance ) : System

Constructs a Gaussian distribution with given mean and given variance.

ProbabilityDensityFunction ( double x ) : double

Gets the probability density function (pdf) for the Gaussian distribution evaluated at point x.

The Probability Density Function (PDF) describes the probability that a given value x will occur.

ZScore ( double x ) : double

Gets the Z-Score for a given value.

메소드 상세

Clone() 공개 메소드

Creates a new object that is a copy of the current instance.
public Clone ( ) : object
리턴 object

DistributionFunction() 공개 메소드

Gets the cumulative distribution function (cdf) for the this distribution evaluated at point x.

The Cumulative Distribution Function (CDF) describes the cumulative probability that a given value or any value smaller than it will occur.

The calculation is computed through the relationship to the function as erfc(-z/sqrt(2)) / 2.

References: http://mathworld.wolfram.com/NormalDistributionFunction.html

public DistributionFunction ( double x ) : double
x double /// A single point in the distribution range.
리턴 double

Fit() 공개 메소드

Fits the underlying distribution to a given set of observations.
public Fit ( double observations, double weights ) : IDistribution
observations double /// The array of observations to fit the model against. ///
weights double /// The weight vector containing the weight for each of the samples. ///
리턴 IDistribution

NormalDistribution() 공개 메소드

Constructs a Gaussian distribution with zero mean and unit variance.
public NormalDistribution ( ) : System
리턴 System

NormalDistribution() 공개 메소드

Constructs a Gaussian distribution with given mean and unit variance.
public NormalDistribution ( double mean ) : System
mean double
리턴 System

NormalDistribution() 공개 메소드

Constructs a Gaussian distribution with given mean and given variance.
public NormalDistribution ( double mean, double variance ) : System
mean double
variance double
리턴 System

ProbabilityDensityFunction() 공개 메소드

Gets the probability density function (pdf) for the Gaussian distribution evaluated at point x.
The Probability Density Function (PDF) describes the probability that a given value x will occur.
public ProbabilityDensityFunction ( double x ) : double
x double A single point in the distribution range. For a /// univariate distribution, this should be a single /// double value. For a multivariate distribution, /// this should be a double array.
리턴 double

ZScore() 공개 메소드

Gets the Z-Score for a given value.
public ZScore ( double x ) : double
x double
리턴 double