Categorical Class |
Discrete Univariate Categorical distribution.
For details about this distribution, see
Wikipedia - Categorical distribution. This
distribution is sometimes called the Discrete distribution.
Inheritance HierarchyNamespace: Altaxo.Calc.Distributions
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3261.0 (4.8.3261.0)
SyntaxC#
public class Categorical : IDiscreteDistribution, IUnivariateDistribution, IDistribution
The Categorical type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | Categorical(Double) | Initializes a new instance of the Categorical class. |
| Categorical(Histogram) | Initializes a new instance of the Categorical class from a histogram. The distribution will not be automatically updated when the histogram changes. The categorical distribution will have one value for each bucket and a probability for that value proportional to the bucket count. |
| Categorical(Double, Random) | Initializes a new instance of the Categorical 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 he mode of the distribution. |
| P | Gets the probability mass vector (non-negative ratios) of the multinomial. |
| 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) |
| InvCDF | Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. |
| InvCDFWithCumulativeDistribution | Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. |
| InverseCumulativeDistribution | Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. |
| IsValidCumulativeDistribution | Checks whether the parameters of the distribution are valid. |
| IsValidProbabilityMass | Checks whether the parameters of the distribution are valid. |
| 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 Binomially distributed random variable. |
| Sample(Double) | Samples one categorical distributed random variable; also known as the Discrete distribution. |
| Sample(Random, Double) | Samples one categorical distributed random variable; also known as the Discrete distribution. |
| Samples | Samples an array of Bernoulli distributed random variables. |
| Samples(Double) | Samples a categorically distributed random variable. |
| 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 categorically distributed random variable. |
| Samples(Random, Int32, Double) | Fills an array with samples generated from the distribution. |
| SamplesWithCumulativeDistribution(Double) | Samples a categorically distributed random variable. |
| SamplesWithCumulativeDistribution(Int32, Double) | Fills an array with samples generated from the distribution. |
| SamplesWithCumulativeDistribution(Random, Double) | Samples a categorically distributed random variable. |
| SamplesWithCumulativeDistribution(Random, Int32, Double) | Fills an array with samples generated from the distribution. |
| SampleWithCumulativeDistribution(Double) | Samples one categorical distributed random variable; also known as the Discrete distribution. |
| SampleWithCumulativeDistribution(Random, Double) | Samples one categorical distributed random variable; also known as the Discrete distribution. |
| ToString |
A string representation of the distribution.
(Overrides ObjectToString) |
Remarks
The distribution is parameterized by a vector of ratios: in other words, the parameter
does not have to be normalized and sum to 1. The reason is that some vectors can't be exactly normalized
to sum to 1 in floating point representation.
See Also