HypergeometricDistribution Class

Represents a hypergeometric distribution.

Definition

Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

[SerializableAttribute]
public class HypergeometricDistribution : DiscreteDistribution

Visual Basic

<SerializableAttribute>
Public Class HypergeometricDistribution
	Inherits DiscreteDistribution

C++/CLI

[SerializableAttribute]
public ref class HypergeometricDistribution : public DiscreteDistribution

[<SerializableAttribute>]
type HypergeometricDistribution = 
    class
        inherit DiscreteDistribution
    end

Inheritance: Object → Distribution → DiscreteDistribution → HypergeometricDistribution

Remarks

The hypergeometric distribution describes the probabilities of obtaining a certain number of tagged elements in a sample of given size out of a population of tagged and untagged elements.

Constructors

HypergeometricDistribution

Constructs a new HypergeometricDistribution object with the specified parameters.

Properties

Entropy	Gets the entropy of the distribution. (Inherited from Distribution)
IsUnimodal	Gets whether the distribution has one or more modes. (Inherited from DiscreteDistribution)
Kurtosis	Gets the kurtosis of the distribution. (Overrides Distribution.Kurtosis)
Mean	Gets the mean or expectation value of the distribution. (Overrides Distribution.Mean)
Mode	Gets the mode of the distribution. (Overrides DiscreteDistribution.Mode)
NumberOfModes	Gets the number of modes of the distribution. (Overrides DiscreteDistribution.NumberOfModes)
NumberOfSamples	Gets the total number of samples taken.
Skewness	Gets the skewness of the distribution. (Overrides Distribution.Skewness)
StandardDeviation	Gets the standard deviation of the distribution. (Inherited from Distribution)
StatisticSymbol	Gets the common symbol to describe a statistic from the distribution. (Inherited from Distribution)
TaggedPopulation	Gets the number of tagged items.
UntaggedPopulation	Gets the number of untagged items.
Variance	Gets the variance of the distribution. (Overrides Distribution.Variance)

Methods

DistributionFunction	Evaluates the cumulative distribution function of the distribution. (Overrides DiscreteDistribution.DistributionFunction(Int32))
Equals	Determines whether the specified object is equal to the current object. (Inherited from Object)
Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object)
GetAllModes	Returns an array that contains all the modes of the distribution. (Overrides DiscreteDistribution.GetAllModes())
GetExpectedHistogram(Double)	Gets a vector whose bins contain the expected number of samples for a given total number of samples.
GetExpectedHistogram(Index<Interval<Int32>>, Double)	Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples. (Inherited from DiscreteDistribution)
GetExpectedHistogram(Index<Int32>, Double)	Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples. (Inherited from DiscreteDistribution)
GetExpectedHistogram(Int32, Int32, Double)	Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples. (Inherited from DiscreteDistribution)
GetHashCode	Serves as the default hash function. (Inherited from Object)
GetRandomSequence()	Returns a sequence of random samples from the distribution. (Inherited from DiscreteDistribution)
GetRandomSequence(Random)	Returns a sequence of random samples from the distribution. (Inherited from DiscreteDistribution)
GetRandomSequence(Random, Int32)	Returns a sequence of random samples of the specified length from the distribution. (Inherited from DiscreteDistribution)
GetType	Gets the Type of the current instance. (Inherited from Object)
InverseDistributionFunction	Returns the inverse of the distribution function. (Inherited from DiscreteDistribution)
LeftTailProbability	Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound. (Inherited from DiscreteDistribution)
LogProbability	Returns the logarithm of the probability of obtaining a specific integer value in the distribution. (Overrides DiscreteDistribution.LogProbability(Int32))
MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
Probability(Int32)	Returns the probability of obtaining a specific integer value in the distribution. (Overrides DiscreteDistribution.Probability(Int32))
Probability(Int32, Int32)	Gets the probability of obtaining a sample that falls within the specified interval from the distribution. (Inherited from DiscreteDistribution)
RightTailProbability	Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound. (Inherited from DiscreteDistribution)
Sample()	Returns a random sample from the distribution. (Inherited from DiscreteDistribution)
Sample(Int32)	Returns a vector of random samples from the distribution. (Inherited from DiscreteDistribution)
Sample(Random)	Returns a random sample from the distribution. (Overrides DiscreteDistribution.Sample(Random))
Sample(Int32, Random)	Returns a vector of random samples from the distribution. (Inherited from DiscreteDistribution)
Sample(Random, Int32[])	Fills an Int32 array with random numbers. (Inherited from DiscreteDistribution)
Sample(Random, Int32[], Int32, Int32)	Fills an Int32 array with random numbers from this DiscreteDistribution. (Inherited from DiscreteDistribution)
Sample(Random, Int32, Int32, Int32)	Returns a single random sample from a binomial distribution with the specified parameters.
ToString	Returns a string that represents the current object. (Overrides Object.ToString())
TwoTailProbability	Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound. (Inherited from DiscreteDistribution)