Module rand::distributions

Sampling from random distributions.

This is a generalization of Rand to allow parameters to control the exact properties of the generated values, e.g. the mean and standard deviation of a normal distribution. The Sample trait is the most general, and allows for generating values that change some state internally. The IndependentSample trait is for generating values that do not need to record state.

Reexports

pub use self::range::Range;

pub use self::gamma::{Gamma, ChiSquared, FisherF, StudentT};

pub use self::normal::{Normal, LogNormal};

pub use self::exponential::Exp;

Modules

exponential	The exponential distribution.
gamma	The Gamma and derived distributions.
normal	The normal and derived distributions.
range	Generating numbers between two others.

Structs

RandSample	A wrapper for generating types that implement Rand via the Sample & IndependentSample traits.
Weighted	A value with a particular weight for use with WeightedChoice.
WeightedChoice	A distribution that selects from a finite collection of weighted items.

Traits

IndependentSample	Samples that do not require keeping track of state.
Sample	Types that can be used to create a random instance of Support.