BinomialDistribution Methods

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(Double) Gets a vector whose bins contain the expected number of samples for a given total number of samples.
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.
(Overrides DiscreteDistribution.LogProbability(Int32))
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, Int32) Returns a single random sample from a binomial distribution with the specified parameters. The probability of a trial resulting in a success is set to 0.5.
Sample(Random, Int32[]) Fills an Int32 array with random numbers.
(Inherited from DiscreteDistribution)
Sample(Random, Int32, Double) Returns a single random sample from a binomial distribution with the specified parameters.
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