Module rand::distributions [−] [src]

Sampling from random distributions.

A distribution may have internal state describing the distribution of generated values; for example Range needs to know its upper and lower bounds. Distributions use the Distribution trait to yield values: call distr.sample(&mut rng) to get a random variable.

Re-exports

pub use self::range::Range;

pub use self::gamma::Gamma;

pub use self::gamma::ChiSquared;

pub use self::gamma::FisherF;

pub use self::gamma::StudentT;

pub use self::normal::Normal;

pub use self::normal::LogNormal;

pub use self::normal::StandardNormal;

pub use self::exponential::Exp;

pub use self::exponential::Exp1;

pub use self::poisson::Poisson;

pub use self::binomial::Binomial;

Modules

binomial	The binomial distribution.
exponential	The exponential distribution.
gamma	The Gamma and derived distributions.
normal	The normal and derived distributions.
poisson	The Poisson distribution.
range	A distribution generating numbers within a given range.

Structs

Alphanumeric	Sample a `char`, uniformly distributed over ASCII letters and numbers: a-z, A-Z and 0-9.
Uniform	A generic random value distribution. Generates values for various types with numerically uniform distribution.
Weighted	A value with a particular weight for use with `WeightedChoice`.
WeightedChoice	A distribution that selects from a finite collection of weighted items.

Traits

Distribution	Types (distributions) that can be used to create a random instance of `T`.
IndependentSample	[ Deprecated ] `Sample`s that do not require keeping track of state.
Sample	[ Deprecated ] Types that can be used to create a random instance of `Support`.