BernoulliDistribution Class

Represents the Bernoulli distribution.

Definition

Namespace: Numerics.NET.Statistics.Distributions
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4
C#
[SerializableAttribute]
public class BernoulliDistribution : DiscreteDistribution
Inheritance
Object  →  Distribution  →  DiscreteDistribution  →  BernoulliDistribution

Remarks

The Bernoulli distribution is a discrete probability distribution that has two possible outcomes: 0 (failure) and 1 (success). The distribution has one parameter: the probability probability of success.

The Bernoulli distribution is the simplest discrete probability distribution. It forms the basis for several other distributions, as shown in the following table.

DistributionDefinition
BinomialDistributionThe number of successes in n trials.
GeometricDistributionThe number of failures before the first success.
NegativeBinomialDistributionThe number of failures before the nth success.

Example

The distribution of heads and tails in a coin toss is a Bernoulli distribution with probability = 0.5. Which of heads or tails corresponds to a successful outcome is arbitrary in this case.

Constructors

BernoulliDistribution Constructs a new BernoulliDistribution with the specified probability of success.

Properties

Capabilities Gets a value that indicates the capabilities of the distribution class.
(Inherited from Distribution)
Entropy Gets the entropy of the distribution.
(Overrides Distribution.Entropy)
IsUnimodal Gets whether the distribution has one or more modes.
(Inherited from DiscreteDistribution)
Kurtosis Gets the kurtosis of the distribution.
(Overrides Distribution.Kurtosis)
Mean Gets the mean or expectation value of the distribution.
(Overrides Distribution.Mean)
Mode Gets the mode of the distribution.
(Overrides DiscreteDistribution.Mode)
NumberOfModes Gets the number of modes of the distribution.
(Overrides DiscreteDistribution.NumberOfModes)
ProbabilityOfSuccess Gets the probability that a trial is successful.
Skewness Gets the skewness of the distribution.
(Overrides Distribution.Skewness)
StandardDeviation Gets the standard deviation of the distribution.
(Inherited from Distribution)
StatisticSymbol Gets the common symbol to describe a statistic from the distribution.
(Inherited from Distribution)
Variance Gets the variance of the distribution.
(Overrides Distribution.Variance)

Methods

DistributionFunction Gets the probability of obtaining an outcome less than or equal to a specified value.
(Overrides DiscreteDistribution.DistributionFunction(Int32))
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
FinalizeAllows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object)
GetAllModes Returns an array that contains all the modes of the distribution.
(Overrides DiscreteDistribution.GetAllModes())
GetExpectedHistogram(Index<Interval<Int32>>, Double) Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples.
(Inherited from DiscreteDistribution)
GetExpectedHistogram(Index<Int32>, Double) Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples.
(Inherited from DiscreteDistribution)
GetExpectedHistogram(Int32, Int32, Double) Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples.
(Inherited from DiscreteDistribution)
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetRandomSequence() Returns a sequence of random samples from the distribution.
(Inherited from DiscreteDistribution)
GetRandomSequence(Random) Returns a sequence of random samples from the distribution.
(Inherited from DiscreteDistribution)
GetRandomSequence(Random, Int32) Returns a sequence of random samples of the specified length from the distribution.
(Inherited from DiscreteDistribution)
GetTypeGets the Type of the current instance.
(Inherited from Object)
InverseDistributionFunction Returns the inverse of the distribution function.
(Overrides DiscreteDistribution.InverseDistributionFunction(Double))
LeftTailProbability Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound.
(Inherited from DiscreteDistribution)
LogProbability Returns the logarithm of the probability of obtaining a specific integer value in the distribution.
(Inherited from DiscreteDistribution)
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Probability(Int32) Returns the probability of obtaining a specific integer value in the distribution.
(Overrides DiscreteDistribution.Probability(Int32))
Probability(Int32, Int32) Gets the probability of obtaining a sample that falls within the specified interval from the distribution.
(Inherited from DiscreteDistribution)
RightTailProbability Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound.
(Inherited from DiscreteDistribution)
Sample() Returns a random sample from the distribution.
(Inherited from DiscreteDistribution)
Sample(Int32) Returns a vector of random samples from the distribution.
(Inherited from DiscreteDistribution)
Sample(Random) Returns a random sample from the distribution.
(Overrides DiscreteDistribution.Sample(Random))
Sample(Int32, Random) Returns a vector of random samples from the distribution.
(Inherited from DiscreteDistribution)
Sample(Random, Double) Returns a single random sample from a Bernoulli distribution with the specified success rate.
Sample(Random, Int32[]) Fills an Int32 array with random numbers.
(Inherited from DiscreteDistribution)
Sample(Random, Int32[], Int32, Int32) Fills an Int32 array with random numbers from this DiscreteDistribution.
(Inherited from DiscreteDistribution)
ToStringReturns a string that represents the current object.
(Overrides Object.ToString())
TwoTailProbability Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound.
(Inherited from DiscreteDistribution)

See Also