C# Class Accord.Statistics.Distributions.Multivariate.MultivariateDiscreteDistribution

Inheritance: DistributionBase, IDistribution, IMultivariateDistribution

Afficher le fichier Open project: atosorigin/Kinect

Méthodes publiques

Méthode	Description
Clone ( ) : object	Creates a new object that is a copy of the current instance.
DistributionFunction ( int 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.
ProbabilityMassFunction ( int x ) : double	Gets the probability mass function (pmf) for this distribution evaluated at point `x`. The Probability Mass Function (PMF) describes the probability that a given value `x` will occur.

Méthode	Description
MultivariateDiscreteDistribution ( int dimension ) : System	Constructs a new MultivariateDiscreteDistribution class.

Méthode	Description
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 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.

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

public abstract Clone ( ) : object
Résultat	object

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 ( int x ) : double
x	int	/// A single point in the distribution range.
Résultat	double

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. ///
Résultat	IDistribution

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. ///
Résultat	IDistribution

Constructs a new MultivariateDiscreteDistribution class.

protected MultivariateDiscreteDistribution ( int dimension ) : System
dimension	int
Résultat	System

Gets the probability mass function (pmf) for this distribution evaluated at point x.

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

public abstract ProbabilityMassFunction ( int x ) : double
x	int	/// A single point in the distribution range.
Résultat	double