Discrete Distribution Class
Definition
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.3
[SerializableAttribute]
public abstract class DiscreteDistribution : Distribution
- Inheritance
- Object → Distribution → DiscreteDistribution
- Derived
Remarks
The distribution of a variable is a description of the relative numbers of times each possible outcome will occur in a number of trials. The function describing the distribution is called the probability function, and the function describing the cumulative probability that a given value or any value smaller than it will occur is called the distribution function.
A discrete probability distribution is a statistical distribution whose variables can take on only discrete values.
This library contains classes for the most common discrete distributions. They are listed in the table below.
Distribution | Definition |
---|---|
Bernoulli | The outcome of a single trial. |
Binomial | The number of successes in N trials. |
Geometric | The number of failures before the first success. |
Hypergeometric | The number of successes in N trials taken from a set with m good outcomes and n bad outcomes. |
Negative | The number of failures before the nth success. |
Poisson | The number of occurrences of an event in a specified unit of space or time. |
Discrete | A distribution with a constant probability over an interval. |
DiscreteDistribution is an abstract base class that cannot be instantiated. To create a continuous distribution of a specific type, instantiate a class derived from DiscreteDistribution.
Notes to inheritors: When you inherit from DiscreteDistribution, you must override the following members: Probability(Int32), DistributionFunction(Int32), Sample(), Mean, and Variance.
Constructors
Discrete | Constructs a new DiscreteDistribution object. |
Properties
Capabilities |
Gets a value that indicates the capabilities of the distribution class.
(Inherited from Distribution) |
Entropy |
Gets the entropy of the distribution.
(Inherited from Distribution) |
IsUnimodal | Gets whether the distribution has one or more modes. |
Kurtosis |
Gets the kurtosis of the distribution.
(Inherited from Distribution) |
Mean |
Gets the mean or expectation value of the distribution.
(Inherited from Distribution) |
Mode | Gets the mode of the distribution. |
Number | Gets the number of modes of the distribution. |
Skewness |
Gets the skewness of the distribution.
(Inherited from Distribution) |
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.
(Inherited from Distribution) |
Methods
Distribution | Gets the probability of obtaining an outcome less than or equal to a specified value. |
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. |
Get | Returns a histogram whose bins contain the expected number of samples from the distribution 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. |
Get | Returns a histogram whose bins contain the expected number of samples from the distribution for a given total number of samples. |
Get | Serves as the default hash function. (Inherited from Object) |
Get | Returns a sequence of random samples from the distribution. |
Get | Returns a sequence of random samples from the distribution. |
Get | Returns a sequence of random samples of the specified length from the distribution. |
Get | Gets the Type of the current instance. (Inherited from Object) |
Inverse | Returns the inverse of the distribution function. |
Left | Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound. |
Log | Returns the logarithm of the probability of obtaining a specific integer value in the distribution. |
Memberwise | Creates a shallow copy of the current Object. (Inherited from Object) |
Probability( | Returns the probability of obtaining a specific integer value in the distribution. |
Probability( | Gets the probability of obtaining a sample that falls within the specified interval from the distribution. |
Right | Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound. |
Sample() | Returns a random sample from the distribution. |
Sample( | Returns a vector of random samples from the distribution. |
Sample( | Returns a random sample from the distribution. |
Sample( | Returns a vector of random samples from the distribution. |
Sample( | Fills an Int32 array with random numbers. |
Sample( | Fills an Int32 array with random numbers from this DiscreteDistribution. |
ToString | Returns a string that represents the current object. (Inherited from Object) |
Two | Gets the probability of obtaining a sample that is less than or less than or equal to the specified upper bound. |