Beta |
Discrete Univariate Beta-Binomial distribution.
The beta-binomial distribution is a family of discrete probability distributions on a finite support of non-negative integers arising
when the probability of success in each of a fixed or known number of Bernoulli trials is either unknown or random.
The beta-binomial distribution is the binomial distribution in which the probability of success at each of n trials is not fixed but randomly drawn from a beta distribution.
It is frequently used in Bayesian statistics, empirical Bayes methods and classical statistics to capture overdispersion in binomial type distributed data.
Wikipedia - Beta-Binomial distribution.
Inheritance HierarchyNamespace: Altaxo.Calc.Distributions
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
SyntaxC#
public class BetaBinomial : IDiscreteDistribution, IUnivariateDistribution, IDistribution
The BetaBinomial type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | BetaBinomial(Int32, Double, Double) | Initializes a new instance of the BetaBinomial class. |
| BetaBinomial(Int32, Double, Double, Random) | Initializes a new instance of the BetaBinomial class. |
Properties| Name | Description | |
|---|---|---|
 | A | |
| B | |
| 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. |
| Minimum | Gets the smallest element in the domain of the distributions which can be represented by an integer. |
| N | |
| RandomSource | |
| 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(Int32, Double, Double) | Tests whether the provided values are valid parameters for this distribution. |
| IsValidParameterSet(Int32, Double, Double, Int32) | 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 BetaBinomial distributed random variable. |
| Sample(Random, Int32, Double, Double) | Samples a BetaBinomial distributed random variable. |
| Samples | Samples an array of BetaBinomial distributed random variables. |
| Samples(Int32) | Fills an array with samples generated from the distribution. |
| Samples(Int32, Double, Double) | Samples an array of BetaBinomial distributed random variables. |
| Samples(Int32, Int32, Double, Double) | Fills an array with samples generated from the distribution. |
| Samples(Random, Int32, Int32, Double, Double) | Fills an array with samples generated from the distribution. |
| ToString |
Returns a String that represents this instance.
(Overrides ObjectToString) |
See Also