## Uses of Interfaceorg.ojalgo.random.Distribution

• Packages that use Distribution
Package Description
org.ojalgo.random
org.ojalgo.random.process
• ### Uses of Distribution in org.ojalgo.random

Subinterfaces of Distribution in org.ojalgo.random
Modifier and Type Interface and Description
`interface ` `ContinuousDistribution`
`interface ` `DiscreteDistribution`
Classes in org.ojalgo.random that implement Distribution
Modifier and Type Class and Description
`class ` `Binomial`
The frequency in aCount indepedent trials, each with probability aProbability, has a binomial distribution.
`class ` `Cauchy`
https://en.wikipedia.org/wiki/Cauchy_distribution
`class ` `Deterministic`
`class ` `Erlang`
Distribution of the sum of aCount random variables with an exponential distribution with parameter aLambda.
`class ` `Exponential`
Distribution of length of life when no aging.
`class ` `Gamma`
Distribution of the sum of aCount random variables with an exponential distribution with parameter aLambda.
`class ` `Geometric`
The number of required trials until an event with probability aProbability occurs has a geometric distribution.
`class ` `LogNormal`
A continuous distribution in which the logarithm of a variable has a normal distribution.
`class ` `Normal`
Under general conditions, the sum of a large number of random variables is approximately normally distributed (the central limit theorem).
`class ` `Poisson`
The Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time and/or space if these events occur with a known average rate and independently of the time since the last event.
`class ` `RandomNumber`
RandomNumber
`class ` `TDistribution`
`class ` `Uniform`
Certain waiting times.
`class ` `Weibull`
Useful as length of life distribution in reliability theory.
• ### Uses of Distribution in org.ojalgo.random.process

Classes in org.ojalgo.random.process with type parameters of type Distribution
Modifier and Type Interface and Description
`interface ` `RandomProcess<D extends Distribution>`
A random/stochastic process is a collection of random variables representing the evolution of some random value over "time".