Categorical Methods |
The Categorical type exposes the following members.
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) |
See Also