Represents the negative binomial distribution.
SystemObject Extreme.Statistics.DistributionsDistribution Extreme.Statistics.DistributionsDiscreteDistribution Extreme.Statistics.DistributionsNegativeBinomialDistribution
Namespace:
Extreme.Statistics.Distributions
Assembly:
Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
[SerializableAttribute]
public class NegativeBinomialDistribution : DiscreteDistribution
<SerializableAttribute>
Public Class NegativeBinomialDistribution
Inherits DiscreteDistribution
[SerializableAttribute]
public ref class NegativeBinomialDistribution : public DiscreteDistribution
[<SerializableAttribute>]
type NegativeBinomialDistribution =
class
inherit DiscreteDistribution
end
The NegativeBinomialDistribution type exposes the following members.
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| Name | Description |
---|
 | DistributionFunction |
Evaluates the cumulative distribution function of the
distribution.
(Overrides DiscreteDistributionDistributionFunction(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.
(Inherited from DiscreteDistribution.) |
 | GetExpectedHistogram(IndexIntervalInt32, 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(IndexInt32, 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 DiscreteDistributionLogProbability(Int32).) |
 | MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
 | Probability(Int32) |
Evaluates the probability function of the distribution.
(Overrides DiscreteDistributionProbability(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 DiscreteDistributionSample(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, Double) |
Returns a single random sample from a negative binomial distribution
with the specified parameters.
|
 | Sample(Random, Int32, Int32, Int32) | (Inherited from DiscreteDistribution.) |
 | ToString | Returns a string that represents the current object. (Overrides ObjectToString.) |
 | 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.) |
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The negative binomial distribution models the number of failures before a specified number of successes
in a series of Bernoulli trials.
A Bernoulli trial is an experiment with two possible outcomes, labeled 'success' and 'failure,'
where the probability of success has a fixed value for all trials.
A negative binomial distribution has two parameters: the NumberOfTrials
and the ProbabilityOfSuccess of an individual trial.
In jury selection, the total number of candidates before 12 jurors have been selected
has a negative binomial distribution.
When playing a video game where the probability of completing a level is constant,
the total number of levels completed before the three lives are used up has a negative binomial distribution.
Reference