DiscreteDistribution Class

[SerializableAttribute]
public abstract class DiscreteDistribution : Distribution

<SerializableAttribute>
Public MustInherit Class DiscreteDistribution
	Inherits Distribution

[SerializableAttribute]
public ref class DiscreteDistribution abstract : public Distribution

[<AbstractClassAttribute>]
[<SerializableAttribute>]
type DiscreteDistribution = 
    class
        inherit Distribution
    end

Inheritance

Object  →  Distribution  →  DiscreteDistribution

Derived

Extreme.Statistics.Distributions.BernoulliDistribution

Extreme.Statistics.Distributions.BinomialDistribution

Extreme.Statistics.Distributions.DiscreteUniformDistribution

Extreme.Statistics.Distributions.GenericDiscreteDistribution

Extreme.Statistics.Distributions.GeometricDistribution

Extreme.Statistics.Distributions.HypergeometricDistribution

Extreme.Statistics.Distributions.LogarithmicSeriesDistribution

Extreme.Statistics.Distributions.NegativeBinomialDistribution

Extreme.Statistics.Distributions.PoissonDistribution

More Less

The distribution of a variable is a description of the relative numbers of times each possible outcome will occur in a number of trials. The function describing the distribution is called the probability function, and the function describing the cumulative probability that a given value or any value smaller than it will occur is called the distribution function.

A discrete probability distribution is a statistical distribution whose variables can take on only discrete values.

This library contains classes for the most common discrete distributions. They are listed in the table below.

DiscreteDistribution is an abstract base class that cannot be instantiated. To create a continuous distribution of a specific type, instantiate a class derived from DiscreteDistribution.

Notes to inheritors: When you inherit from DiscreteDistribution, you must override the following members: Probability(Int32), DistributionFunction(Int32), Sample(), Mean, and Variance.

Reference