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  • Extreme.Statistics.Distributions
    • ArcsineDistribution Class
    • BernoulliDistribution Class
    • BetaDistribution Class
    • BinomialDistribution Class
    • CauchyDistribution Class
    • ChiSquareDistribution Class
    • ContinuousDistribution Class
    • ContinuousUniformDistribution Class
    • DirichletDistribution Class
    • DiscreteDistribution Class
    • DiscreteDistribution(T) Class
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    • Distribution Class
    • ErlangDistribution Class
    • EstimationMethod Enumeration
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    • FDistribution Class
    • GammaDistribution Class
    • GaussianMixtureDistribution Class
    • GeneralizedParetoDistribution Class
    • GenericDiscreteDistribution Class
    • GeometricDistribution Class
    • 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
    • ParetoDistribution Class
    • ParetoDistributionVariant Enumeration
    • PertDistribution Class
    • PiecewiseDistribution Class
    • PoissonDistribution Class
    • RandomExtensions Class
    • RayleighDistribution Class
    • StudentTDistribution Class
    • TransformedBetaDistribution Class
    • TransformedGammaDistribution Class
    • TriangularDistribution Class
    • TruncatedDistribution Class
    • WeibullDistribution Class
    • WishartDistribution Class
  • ContinuousDistribution Class
    • ContinuousDistribution Constructor
    • Properties
    • Methods

ContinuousDistribution Class

Extreme Optimization Numerical Libraries for .NET Professional
Represents a continuous probability distribution.
Inheritance Hierarchy

SystemObject
  Extreme.Statistics.DistributionsDistribution
    Extreme.Statistics.DistributionsContinuousDistribution
      More...

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

C#
VB
C++
F#
Copy
[SerializableAttribute]
public abstract class ContinuousDistribution : Distribution
<SerializableAttribute>
Public MustInherit Class ContinuousDistribution
	Inherits Distribution
[SerializableAttribute]
public ref class ContinuousDistribution abstract : public Distribution
[<AbstractClassAttribute>]
[<SerializableAttribute>]
type ContinuousDistribution =  
    class
        inherit Distribution
    end

The ContinuousDistribution type exposes the following members.

Constructors

  NameDescription
Protected methodContinuousDistribution
Constructs a new ContinuousDistribution object.
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Properties

  NameDescription
Public propertyEntropy
Gets the entropy of the distribution.
(Inherited from Distribution.)
Public propertyInterQuartileRange
Returns the inter-quartile range of this distribution.
Public propertyIsSymmetrical
Gets whether the distribution is known to be symmetrical around the mean.
Public propertyIsUnimodal
Gets whether the distribution has one or more modes.
Public propertyKurtosis
Gets the kurtosis of the distribution.
(Inherited from Distribution.)
Public propertyMean
Gets the mean or expectation value of the distribution.
(Inherited from Distribution.)
Public propertyMedian
Gets the median of the distribution.
Public propertyMode
Gets the mode of the distribution.
Public propertyNumberOfModes
Gets the number of modes of the distribution.
Public propertySkewness
Gets the skewness of the distribution.
(Inherited from Distribution.)
Public propertyStandardDeviation
Gets the standard deviation of the distribution.
(Inherited from Distribution.)
Public propertyStatisticSymbol
Gets the common symbol to describe a statistic from the distribution.
(Inherited from Distribution.)
Public propertySupport
Gets the support of the distribution.
Public propertyVariance
Gets the variance of the distribution.
(Inherited from Distribution.)
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Methods

  NameDescription
Public methodCdf
Evaluates the cumulative distribution function (CDF) of this distribution for the specified value.
Public methodDistributionFunction
Evaluates the cumulative distribution function (CDF) of this distribution for the specified value.
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 methodGetAllModes
Returns an array that contains all the modes of the distribution.
Public methodGetExpectationValue(FuncDouble, Double)
Returns the expectation value of a function.
Public methodGetExpectationValue(FuncDouble, Double, Double, Double)
Returns the un-normalized expectation value of a function over the specified interval.
Public methodGetExpectedHistogram(Double, Double)
Gets a vector containing a histogram of the expected number of samples for a given total number of samples.
Public methodGetExpectedHistogram(IntervalIndexDouble, Double)
Gets a vector containing a histogram of the expected number of samples for a given total number of samples.
Public methodGetExpectedHistogram(Double, Double, Int32, Double)
Gets a vector whose bins contain the expected number of samples 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.)
Public methodHazardFunction
Returns the probability of failure at the specified value.
Public methodInverseCdf
Returns the inverse of the DistributionFunction(Double).
Public methodInverseDistributionFunction
Returns the inverse of the DistributionFunction(Double).
Public methodLeftTailProbability
Returns the probability that a sample from the distribution is less than the specified value.
Public methodLogProbabilityDensityFunction
Returns the logarithm of the probability density function (PDF) of this distribution for the specified value.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodMomentFunction
Returns the value of the moment function of the specified order.
Public methodPdf
Returns the value of the probability density function (PDF) of this distribution for the specified value.
Public methodProbability
Returns the probability that a sample taken from the distribution lies inside the specified interval.
Public methodProbabilityDensityFunction
Returns the value of the probability density function (PDF) of this distribution for the specified value.
Public methodRightTailProbability
Returns the probability that a sample from the distribution is larger than the specified value.
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 methodSampleInto(Random, IListDouble)
Fills a list with random numbers from the distribution.
Public methodSampleInto(Random, IListDouble, Int32, Int32)
Fills part of a list with random numbers from the distribution.
Public methodSurvivorDistributionFunction
Evaluates the survivor distribution function (SDF) of this distribution for the specified value.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Public methodTwoTailedProbability
Returns the probability that a sample from the distribution deviates from the mean more than the specified value.
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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, 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 continuous probability distribution is a statistical distribution whose variables can take on any value within a certain interval. This interval may be infinite.

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

DistributionDefinition
BetaDistributionThe beta distribution.
CauchyDistributionThe Cauchy distribution.
ContinuousUniformDistributionThe continuous uniform distribution.
ErlangDistributionThe Erlang distribution.
ExponentialDistributionThe exponential distribution.
FDistributionThe F distribution.
GammaDistributionThe gamma distribution.
GumbelDistributionThe Gumbel or extreme value distribution.
LaplaceDistributionThe Laplace distribution.
LogisticDistributionThe logistic distribution.
LognormalDistributionThe log-normal distribution.
NormalDistributionThe normal distribution.
ParetoDistributionThe Pareto distribution.
RayleighDistributionThe Rayleigh distribution.
StudentTDistributionThe student-t distribution.
TriangularDistributionThe triangular distribution.
WeibullDistributionThe Weibull distribution.

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

Notes to inheritors: When you inherit from ContinuousDistribution, you must override the following members: ProbabilityDensityFunction(Double), DistributionFunction(Double), Mean and Variance. You should also override the following methods: Sample, Skewness, Kurtosis.

See Also

Reference

Extreme.Statistics.Distributions Namespace
Inheritance Hierarchy

SystemObject
  Extreme.Statistics.DistributionsDistribution
    Extreme.Statistics.DistributionsContinuousDistribution
      Extreme.Statistics.DistributionsArcsineDistribution
      Extreme.Statistics.DistributionsBetaDistribution
      Extreme.Statistics.DistributionsCauchyDistribution
      Extreme.Statistics.DistributionsChiSquareDistribution
      Extreme.Statistics.DistributionsContinuousUniformDistribution
      Extreme.Statistics.DistributionsExponentialDistribution
      Extreme.Statistics.DistributionsFDistribution
      Extreme.Statistics.DistributionsGammaDistribution
      Extreme.Statistics.DistributionsGeneralizedParetoDistribution
      Extreme.Statistics.DistributionsGumbelDistribution
      Extreme.Statistics.DistributionsHyperbolicDistribution
      Extreme.Statistics.DistributionsInverseChiSquareDistribution
      Extreme.Statistics.DistributionsInverseGammaDistribution
      Extreme.Statistics.DistributionsInverseGaussianDistribution
      Extreme.Statistics.DistributionsInverseWeibullDistribution
      Extreme.Statistics.DistributionsJohnsonDistribution
      Extreme.Statistics.DistributionsLaplaceDistribution
      Extreme.Statistics.DistributionsLogisticDistribution
      Extreme.Statistics.DistributionsLogLogisticDistribution
      Extreme.Statistics.DistributionsLognormalDistribution
      Extreme.Statistics.DistributionsMaxwellDistribution
      Extreme.Statistics.DistributionsNonCentralBetaDistribution
      Extreme.Statistics.DistributionsNonCentralChiSquareDistribution
      Extreme.Statistics.DistributionsNonCentralFDistribution
      Extreme.Statistics.DistributionsNonCentralStudentTDistribution
      Extreme.Statistics.DistributionsNormalDistribution
      Extreme.Statistics.DistributionsNormalInverseGaussianDistribution
      Extreme.Statistics.DistributionsParetoDistribution
      Extreme.Statistics.DistributionsPiecewiseDistribution
      Extreme.Statistics.DistributionsStudentTDistribution
      Extreme.Statistics.DistributionsTransformedBetaDistribution
      Extreme.Statistics.DistributionsTransformedGammaDistribution
      Extreme.Statistics.DistributionsTriangularDistribution
      Extreme.Statistics.DistributionsTruncatedDistribution
      Extreme.Statistics.DistributionsWeibullDistribution
      Extreme.Statistics.TestsAndersonDarlingDistribution
      Extreme.Statistics.TestsStudentizedRangeDistribution

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