Hypergeometric Class |
public class Hypergeometric : IDiscreteDistribution, IUnivariateDistribution, IDistribution
The Hypergeometric type exposes the following members.
Name | Description | |
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Hypergeometric(Int32, Int32, Int32) | Initializes a new instance of the Hypergeometric class. | |
Hypergeometric(Int32, Int32, Int32, Random) | Initializes a new instance of the Hypergeometric class. |
Name | Description | |
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Draws | Gets the number of draws without replacement (n). | |
Entropy | Gets the entropy of the distribution. | |
Maximum | Gets the maximum of the distribution. | |
Mean | Gets the mean of the distribution. | |
Median | Gets the median of the distribution. | |
Minimum | Gets the minimum of the distribution. | |
Mode | Gets the mode of the distribution. | |
Population | Gets the size of the population (N). | |
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. | |
Success | Gets the number successes within the population (K, M). | |
Variance | Gets the variance of the distribution. |
Name | Description | |
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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 Hypergeometric distributed random variable. | |
Sample(Int32, Int32, Int32) | Samples a random variable. | |
Sample(Random, Int32, Int32, Int32) | Samples a random variable. | |
Samples | Samples an array of Hypergeometric distributed random variables. | |
Samples(Int32) | Fills an array with samples generated from the distribution. | |
Samples(Int32, Int32, Int32) | Samples a sequence of this random variable. | |
Samples(Int32, Int32, Int32, Int32) | Fills an array with samples generated from the distribution. | |
Samples(Random, Int32, Int32, Int32) | Samples a sequence of this random variable. | |
Samples(Random, Int32, Int32, Int32, Int32) | Fills an array with samples generated from the distribution. | |
ToString |
Returns a String that represents this instance.
(Overrides ObjectToString) |