Conway |
Discrete Univariate Conway-Maxwell-Poisson distribution.
The Conway-Maxwell-Poisson distribution is a generalization of the Poisson, Geometric and Bernoulli distributions. It is parameterized by two real numbers "lambda" and "nu". For
- nu = 0 the distribution reverts to a Geometric distribution
- nu = 1 the distribution reverts to the Poisson distribution
- nu -> infinity the distribution converges to a Bernoulli distribution
Inheritance HierarchyNamespace: Altaxo.Calc.Distributions
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
SyntaxC#
public class ConwayMaxwellPoisson : IDiscreteDistribution, IUnivariateDistribution, IDistribution
The ConwayMaxwellPoisson type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | ConwayMaxwellPoisson(Double, Double) | Initializes a new instance of the ConwayMaxwellPoisson class. |
| ConwayMaxwellPoisson(Double, Double, Random) | Initializes a new instance of the ConwayMaxwellPoisson class. |
Properties| Name | Description | |
|---|---|---|
 | Entropy | Gets the entropy of the distribution. |
| Lambda | Gets the lambda (λ) parameter. 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 |
| Nu | Gets the rate of decay (ν) parameter. Range: ν ≥ 0. |
| RandomSource | Gets or sets 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. |
Methods| 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 Conway-Maxwell-Poisson distributed random variable. |
| Sample(Double, Double) | Samples a random variable. |
| Sample(Random, Double, Double) | Samples a random variable. |
| Samples | Samples a sequence of a Conway-Maxwell-Poisson distributed random variables. |
| Samples(Int32) | Fills an array with samples generated from the distribution. |
| Samples(Double, Double) | Samples a sequence of this random variable. |
| Samples(Int32, Double, Double) | Fills an array with samples generated from the distribution. |
| Samples(Random, Double, Double) | Samples a sequence of this random variable. |
| Samples(Random, Int32, Double, Double) | Fills an array with samples generated from the distribution. |
| ToString |
Returns a String that represents this instance.
(Overrides ObjectToString) |
See Also