BernoulliDistribution Class |
Represents a Bernoulli distribution.
Inheritance HierarchySystemObject
Meta.Numerics.Statistics.DistributionsUnivariateDistribution
Meta.Numerics.Statistics.DistributionsDiscreteDistribution
Meta.Numerics.Statistics.DistributionsBernoulliDistribution
Meta.Numerics.Statistics.DistributionsUnivariateDistribution
Meta.Numerics.Statistics.DistributionsDiscreteDistribution
Meta.Numerics.Statistics.DistributionsBernoulliDistribution
Namespace: Meta.Numerics.Statistics.Distributions
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.1.4
SyntaxThe BernoulliDistribution type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | BernoulliDistribution |
Initializes a new Bernoulli distribution.
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Properties| Name | Description | |
|---|---|---|
 | ExcessKurtosis |
Gets the excess kurtosis of the distribution.
(Overrides UnivariateDistributionExcessKurtosis.) |
| Mean |
Gets the mean of the distribution.
(Overrides DiscreteDistributionMean.) |
| Skewness |
Gets the skewness of the distribution.
(Overrides UnivariateDistributionSkewness.) |
| StandardDeviation |
Gets the standard deviation of the distribution.
(Inherited from UnivariateDistribution.) |
| Support |
Gets the interval over which the distribution is non-vanishing.
(Overrides DiscreteDistributionSupport.) |
| Variance |
Gets the variance of the distribution.
(Overrides UnivariateDistributionVariance.) |
Methods| Name | Description | |
|---|---|---|
| CentralMoment |
Gets a central moment of the distribution.
(Overrides DiscreteDistributionCentralMoment(Int32).) |
| Cumulant |
Computes a cumulant of the distribution.
(Inherited from UnivariateDistribution.) |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) |
| ExpectationValue |
Computes the expectation value of an artibrary function.
(Overrides DiscreteDistributionExpectationValue(FuncInt32, Double).) |
 | FitToSample |
Finds the Bernoulli distribution that best fits the given counts.
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| GetHashCode | Serves as the default hash function. (Inherited from Object.) |
| GetRandomValue |
Produces a random integer drawn from the distribution.
(Inherited from DiscreteDistribution.) |
| GetType | Gets the Type of the current instance. (Inherited from Object.) |
| InverseLeftProbability |
Computes the value corresponding to the given percentile.
(Overrides DiscreteDistributionInverseLeftProbability(Double).) |
| LeftExclusiveProbability |
Computes the probability of obtaining a value less than the given value.
(Overrides DiscreteDistributionLeftExclusiveProbability(Int32).) |
| LeftInclusiveProbability |
Computes the probability of obtaining a value less than or equal to the given value.
(Inherited from DiscreteDistribution.) |
| ProbabilityMass |
Returns the probability of the obtaining the given value.
(Overrides DiscreteDistributionProbabilityMass(Int32).) |
| RawMoment |
Gets a raw moment of the distribution.
(Overrides DiscreteDistributionRawMoment(Int32).) |
| RightExclusiveProbability |
Computes the probability of obtaining a value greater than the given value.
(Overrides DiscreteDistributionRightExclusiveProbability(Int32).) |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
RemarksA Bernoulli distribution describes a trial with two possible outcomes. These outcomes are usually called "success" and "failure", but the same framework is applicable to any binary outcome: right or left, true or false, male or female, dead or alive, etc. We represent the outcomes by 0 and 1, which are the only two integers for which the Bernoulli probability does not vanish.
When multiple, independent Bernoulli trials are conducted, the binomial distribution (BinomialDistribution) describes the probability of obtaining any particular number of successes.
See Also