Binomial Distribution Class
Represents the binomial distribution.
Definition
Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
C#
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
[SerializableAttribute]
public class BinomialDistribution : DiscreteDistribution
- Inheritance
- Object → Distribution → DiscreteDistribution → BinomialDistribution
Remarks
The binomial distribution Binomial(n, probability) characterizes the probability of the number of successes in a variable of n trials, each having a probability probability of being successful.
If n = 1, the binomial distribution reduces to the BernoulliDistribution.
Example
The number of dice showing a six when rolling N
dice has a biomial distribution with n = N
and probability = 1/6. Notice that it doesn't matter if the
trials are run simultaneously or in succession.
Constructors
Binomial | Constructs a new BinomialDistribution with the specified number of trials. The probability of success is set to 0.5. |
Binomial | Estimates the parameters of the distribution of a variable assuming it follows a binomial distribution. |
Binomial | Estimates the parameters of the distribution of a variable assuming it follows a binomial distribution. |
Binomial | Constructs a new BinomialDistribution with the specified number of trials and probability of success. |
Properties
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) |
Number |
Gets the number of modes of the distribution.
(Overrides DiscreteDistribution.NumberOfModes) |
Number | Gets the number of trials. |
Probability | Gets the probability that a trial is successful. |
Skewness |
Gets the skewness of the distribution.
(Overrides Distribution.Skewness) |
Standard |
Gets the standard deviation of the distribution.
(Inherited from Distribution) |
Statistic |
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
Distribution |
Evaluates the cumulative distribution function of the
distribution.
(Overrides DiscreteDistribution.DistributionFunction(Int32)) |
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) |
Get |
Returns an array that contains all the modes of the distribution.
(Overrides DiscreteDistribution.GetAllModes()) |
Get | Gets a vector whose bins contain the expected number of samples for a given total number of samples. |
Get |
Returns a histogram whose bins contain the expected number of samples
from the distribution for a given total number of samples.
(Inherited from DiscreteDistribution) |
Get |
Returns a histogram whose bins contain the expected number of samples
from the distribution for a given total number of samples.
(Inherited from DiscreteDistribution) |
Get |
Returns a histogram whose bins contain the expected number of samples
from the distribution for a given total number of samples.
(Inherited from DiscreteDistribution) |
GetHashCode | Serves as the default hash function. (Inherited from Object) |
Get |
Returns a sequence of random samples from the distribution.
(Inherited from DiscreteDistribution) |
Get |
Returns a sequence of random samples from the distribution.
(Inherited from DiscreteDistribution) |
Get |
Returns a sequence of random samples of the specified length from the distribution.
(Inherited from DiscreteDistribution) |
GetType | Gets the Type of the current instance. (Inherited from Object) |
Inverse |
Returns the inverse of the distribution function.
(Overrides DiscreteDistribution.InverseDistributionFunction(Double)) |
Left |
Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound.
(Inherited from DiscreteDistribution) |
Log |
Returns the logarithm of the probability of obtaining
a specific integer value in the distribution.
(Overrides DiscreteDistribution.LogProbability(Int32)) |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) |
Probability( |
Evaluates the probability function of the distribution.
(Overrides DiscreteDistribution.Probability(Int32)) |
Probability( |
Gets the probability of obtaining a sample that falls
within the specified interval from the distribution.
(Inherited from DiscreteDistribution) |
Right |
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( |
Returns a vector of random samples from the distribution.
(Inherited from DiscreteDistribution) |
Sample( |
Returns a random sample from the distribution.
(Overrides DiscreteDistribution.Sample(Random)) |
Sample( |
Returns a vector of random samples from the distribution.
(Inherited from DiscreteDistribution) |
Sample( | 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( |
Fills an Int32 array with random numbers.
(Inherited from DiscreteDistribution) |
Sample( | Returns a single random sample from a binomial distribution with the specified parameters. |
Sample( |
Fills an Int32 array with random numbers from this DiscreteDistribution.
(Inherited from DiscreteDistribution) |
ToString | Returns a string that represents the current object. (Overrides Object.ToString()) |
Two |
Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound.
(Inherited from DiscreteDistribution) |