Poisson Class |
public class Poisson : IDiscreteDistribution, IUnivariateDistribution, IDistribution
The Poisson type exposes the following members.
Name | Description | |
---|---|---|
Poisson(Double) | Initializes a new instance of the Poisson class. | |
Poisson(Double, Random) | Initializes a new instance of the Poisson class. |
Name | Description | |
---|---|---|
Entropy | Gets the entropy of the distribution. | |
Lambda | Gets the Poisson distribution parameter λ. Range: λ > 0. | |
Maximum | Gets the largest element in the domain of the distributions which can be represented by an integer. | |
Mean | Gets the mean of the distribution. | |
Median | Gets the median of the distribution. | |
Minimum | Gets the smallest element in the domain of the distributions which can be represented by an integer. | |
Mode | Gets the mode of the distribution. | |
RandomSource | Gets the random number generator which is used to draw random samples. | |
Skewness | Gets the skewness of the distribution. | |
StdDev | Gets the standard deviation of the distribution. | |
Variance | Gets the variance of the distribution. |
Name | Description | |
---|---|---|
CDF | Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). | |
CumulativeDistribution | Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). | |
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) | |
GetHashCode | Serves as the default hash function. (Inherited from Object) | |
GetType | Gets the Type of the current instance. (Inherited from Object) | |
IsValidParameterSet | Tests whether the provided values are valid parameters for this distribution. | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
PMF | Computes the probability mass (PMF) at k, i.e. P(X = k). | |
PMFLn | Computes the log probability mass (lnPMF) at k, i.e. ln(P(X = k)). | |
Probability | Computes the probability mass (PMF) at k, i.e. P(X = k). | |
ProbabilityLn | Computes the log probability mass (lnPMF) at k, i.e. ln(P(X = k)). | |
Sample | Samples a Poisson distributed random variable. | |
Sample(Double) | Samples a Poisson distributed random variable. | |
Sample(Random, Double) | Samples a Poisson distributed random variable. | |
Samples | Samples an array of Poisson distributed random variables. | |
Samples(Double) | Samples a sequence of Poisson distributed random variables. | |
Samples(Int32) | Fills an array with samples generated from the distribution. | |
Samples(Int32, Double) | Fills an array with samples generated from the distribution. | |
Samples(Random, Double) | Samples a sequence of Poisson distributed random variables. | |
Samples(Random, Int32, Double) | Fills an array with samples generated from the distribution. | |
ToString |
Returns a String that represents this instance.
(Overrides ObjectToString) |
Distribution is described at Wikipedia - Poisson distribution.
Knuth's method is used to generate Poisson distributed random variables.
f(x) = exp(-λ)*λ^x/x!;