Zipf Class |
Discrete Univariate Zipf distribution.
Zipf's law, an empirical law formulated using mathematical statistics, refers to the fact
that many types of data studied in the physical and social sciences can be approximated with
a Zipfian distribution, one of a family of related discrete power law probability distributions.
For details about this distribution, see
Wikipedia - Zipf distribution.
Inheritance HierarchyNamespace: Altaxo.Calc.Distributions
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
SyntaxC#
public class Zipf : IDiscreteDistribution, IUnivariateDistribution, IDistribution
The Zipf type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | Zipf(Double, Int32) | Initializes a new instance of the Zipf class. |
| Zipf(Double, Int32, Random) | Initializes a new instance of the Zipf class. |
Properties| Name | Description | |
|---|---|---|
 | Entropy | Gets the entropy of the distribution. |
| 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. |
| N | Gets or sets the n parameter of the distribution. |
| RandomSource | Gets or sets the random number generator which is used to draw random samples. |
| S | Gets or sets the s parameter of the distribution. |
| 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 | Draws a random sample from the distribution. |
| Sample(Double, Int32) | Samples a random variable. |
| Sample(Random, Double, Int32) | Samples a random variable. |
| Samples | Samples an array of zipf distributed random variables. |
| Samples(Int32) | Fills an array with samples generated from the distribution. |
| Samples(Double, Int32) | Samples a sequence of this random variable. |
| Samples(Int32, Double, Int32) | Fills an array with samples generated from the distribution. |
| Samples(Random, Double, Int32) | Samples a sequence of this random variable. |
| Samples(Random, Int32, Double, Int32) | Fills an array with samples generated from the distribution. |
| ToString |
A string representation of the distribution.
(Overrides ObjectToString) |
See Also