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  • Extreme.Statistics.Distributions
    • ArcsineDistribution Class
    • BernoulliDistribution Class
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    • GumbelDistribution Class
    • HyperbolicDistribution Class
    • HypergeometricDistribution Class
    • InverseChiSquareDistribution Class
    • InverseGammaDistribution Class
    • InverseGaussianDistribution Class
    • InverseWeibullDistribution Class
    • JohnsonDistribution Class
    • JohnsonDistributionType Enumeration
    • LaplaceDistribution Class
    • LogarithmicSeriesDistribution Class
    • LogisticDistribution Class
    • LogLogisticDistribution Class
    • LognormalDistribution Class
    • MaxwellDistribution Class
    • MultivariateContinuousDistribution Class
    • MultivariateNormalDistribution Class
    • NegativeBinomialDistribution Class
    • NonCentralBetaDistribution Class
    • NonCentralChiSquareDistribution Class
    • NonCentralFDistribution Class
    • NonCentralStudentTDistribution Class
    • NormalDistribution Class
    • NormalInverseGaussianDistribution Class
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    • ParetoDistributionVariant Enumeration
    • PertDistribution Class
    • PiecewiseDistribution Class
    • PoissonDistribution Class
    • RandomExtensions Class
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  • DiscreteDistribution(T) Class
    • DiscreteDistribution(T) Constructors
    • Properties
    • Methods

DiscreteDistributionT Class

Extreme Optimization Numerical Libraries for .NET Professional
Represents a probability distribution over a countable set of objects.
Inheritance Hierarchy

SystemObject
  Extreme.Statistics.DistributionsDiscreteDistributionT

Namespace:  Extreme.Statistics.Distributions
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
Syntax

C#
VB
C++
F#
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[SerializableAttribute]
public class DiscreteDistribution<T>
<SerializableAttribute>
Public Class DiscreteDistribution(Of T)
[SerializableAttribute]
generic<typename T>
public ref class DiscreteDistribution
[<SerializableAttribute>]
type DiscreteDistribution<'T> =  class end

Type Parameters

T

The DiscreteDistributionT type exposes the following members.

Constructors

  NameDescription
Public methodDiscreteDistributionT(HistogramT)
Constructs a new DiscreteDistributionT object.
Public methodDiscreteDistributionT(IListT, IListDouble)
Constructs a new DiscreteDistributionT object.
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Properties

  NameDescription
Public propertyItems
Gets the set of items in the distribution.
Public propertyProbabilities
Gets the probabilities of the items in the distribution.
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Methods

  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetExpectedHistogram
Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples.
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetRandomSequence
Returns a sequence of random samples from the distribution.
Public methodGetRandomSequence(Random)
Returns a sequence of random samples from the distribution.
Public methodGetRandomSequence(Random, Int32)
Returns a sequence of random samples of the specified length from the distribution.
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodProbability
Returns the probability of obtaining a specific item in the distribution.
Public methodSample
Returns a random sample from the distribution.
Public methodSample(Int32)
Returns a vector of random samples from the distribution.
Public methodSample(Random)
Returns a random sample from the distribution.
Public methodSample(Int32, Random)
Returns a vector of random samples from the distribution.
Public methodSample(Random, T)
Fills an array with random samples.
Public methodSample(Random, T, Int32, Int32)
Fills an array with random samples from this DiscreteDistributionT.
Public methodSampleLevel
Returns the level index of a random sample from the distribution.
Public methodSampleLevels
Fills an array with the level indexes of random samples from this DiscreteDistributionT.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Remarks

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.

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

See Also

Reference

Extreme.Statistics.Distributions Namespace

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