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

상속: DistributionBase, IDistribution, IUnivariateDistribution
파일 보기 프로젝트 열기: atosorigin/Kinect 1 사용 예제들

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.

Fit ( double observations ) : IDistribution

Fits the underlying distribution to a given set of observations.

Fit ( double observations, double weights ) : IDistribution

Fits the underlying distribution to a given set of observations.

ProbabilityDensityFunction ( double x ) : double

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

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

비공개 메소드들

메소드 설명
IDistribution ( Array observations ) : IDistribution

Fits the underlying distribution to a given set of observations.

Although both double[] and double[][] arrays are supported, providing a double[] for a multivariate distribution or a double[][] for a univariate distribution may have a negative impact in performance.

IDistribution ( Array observations, double weights ) : IDistribution

Fits the underlying distribution to a given set of observations.

Although both double[] and double[][] arrays are supported, providing a double[] for a multivariate distribution or a double[][] for a univariate distribution may have a negative impact in performance.

IDistribution ( ) : double

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

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

메소드 상세

Clone() 공개 추상적인 메소드

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

DistributionFunction() 공개 추상적인 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.
public abstract 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 ) : IDistribution
observations double /// The array of observations to fit the model against. ///
리턴 IDistribution

Fit() 공개 추상적인 메소드

Fits the underlying distribution to a given set of observations.
public abstract 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

ProbabilityDensityFunction() 공개 추상적인 메소드

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