NegativeBinomialDistribution Class

Represents a negative binomial distribution.

Definition

Namespace: Meta.Numerics.Statistics.Distributions
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.2.0+6d77d64445f7d5d91b12e331399c4362ecb25333
C#
public sealed class NegativeBinomialDistribution : DiscreteDistribution
Inheritance
Object    UnivariateDistribution    DiscreteDistribution    NegativeBinomialDistribution

Remarks

Consider a series of independent, repeated Bernoulli trials, each of which results in success with probability p or failure with probability 1-p. If one repeats the trials until r failures occur, the negative binomial distribution gives the probability of having seen k successes before the rth failure.

Keep in mind that there are several different conventions for the meaning of r, p, and k. The most common are that k denotes the number of successes before the rth failure (used here and in the referenced Wikipedia article), and that k denotes the number of failures before the rth success (used by Mathematica). Since these two conventions simply switch success and failure, they can be interconverted by interchanging p and 1-p.

Constructors

NegativeBinomialDistribution Initializes a new negative binomial distribution.

Properties

ExcessKurtosis Gets the excess kurtosis of the distribution.
(Inherited from UnivariateDistribution)
Mean Gets the mean of the distribution.
(Overrides DiscreteDistributionMean)
Skewness Gets the skewness of the distribution.
(Overrides UnivariateDistributionSkewness)
StandardDeviation Gets the standard deviation of the distribution.
(Overrides UnivariateDistributionStandardDeviation)
Support Gets the interval over which the distribution is non-vanishing.
(Overrides DiscreteDistributionSupport)
Variance Gets the variance of the distribution.
(Overrides UnivariateDistributionVariance)

Methods

CentralMoment Gets a central moment of the distribution.
(Inherited from DiscreteDistribution)
Cumulant Computes a cumulant of the distribution.
(Inherited from UnivariateDistribution)
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
ExpectationValue Computes the expectation value of an artibrary function.
(Inherited from DiscreteDistribution)
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetRandomValue Produces a random integer drawn from the distribution.
(Inherited from DiscreteDistribution)
GetTypeGets the Type of the current instance.
(Inherited from Object)
InverseLeftProbability Computes the value corresponding to the given percentile.
(Overrides DiscreteDistributionInverseLeftProbability(Double))
LeftExclusiveProbability Computes the probability of obtaining a value less than the given value.
(Overrides DiscreteDistributionLeftExclusiveProbability(Int32))
LeftInclusiveProbability Computes the probability of obtaining a value less than or equal to the given value.
(Overrides DiscreteDistributionLeftInclusiveProbability(Int32))
ProbabilityMass Returns the probability of the obtaining the given value.
(Overrides DiscreteDistributionProbabilityMass(Int32))
RawMoment Gets a raw moment of the distribution.
(Overrides DiscreteDistributionRawMoment(Int32))
RightExclusiveProbability Computes the probability of obtaining a value greater than the given value.
(Overrides DiscreteDistributionRightExclusiveProbability(Int32))
ToStringReturns a string that represents the current object.
(Inherited from Object)

See Also