PoissonDistribution Class

Represents a Poisson distribution.

Definition

Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
C#
[SerializableAttribute]
public class PoissonDistribution : DiscreteDistribution
Inheritance
Object  →  Distribution  →  DiscreteDistribution  →  PoissonDistribution

Remarks

The Poisson distribution models the number of occurrances of an event where each event has a constant probability of occurring. It is closely related to the exponential distribution, which models the time between successive occurrances.

The Poisson distribution has one parameter: the mean number of occurrances per unit time.

Example

The number of cars passing a road that is not too busy follows a Poisson distribution..

The number of failures of a piece of equipment that is replaced with identical copies when it fails follows a Poisson distribution.

Constructors

PoissonDistribution(Double) Constructs a new PoissonDistribution.
PoissonDistribution(Vector<Double>) Estimates the parameters of the distribution of a variable assuming it follows a Poisson distribution.

Properties

Entropy Gets the entropy of the distribution.
(Overrides Distribution.Entropy)
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)
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)
Variance Gets the variance of the distribution.
(Overrides Distribution.Variance)

Methods

DistributionFunction Evaluates the cumulative distribution function of the distribution.
(Overrides DiscreteDistribution.DistributionFunction(Int32))
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
FinalizeAllows 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(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)
GetHashCodeServes 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)
GetTypeGets 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))
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Probability(Int32) Evaluates the probability function of 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, Double) Gets a single sample from the Poisson distribution with the specified mean.
Sample(Random, Int32[], Int32, Int32) Fills an Int32 array with random numbers from this DiscreteDistribution.
(Inherited from DiscreteDistribution)
ToStringReturns 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)

See Also