Crate rand_distr

Expand description

Generating random samples from probability distributions.

Re-exports

This crate is a super-set of the rand::distributions module. See the rand::distributions module documentation for an overview of the core Distribution trait and implementations.

The following are re-exported:

The Distribution trait and DistIter helper type
The Standard, Alphanumeric, Uniform, OpenClosed01, Open01, Bernoulli, and WeightedIndex distributions

Distributions

This crate provides the following probability distributions:

Related to real-valued quantities that grow linearly (e.g. errors, offsets):
- Normal distribution, and StandardNormal as a primitive
- SkewNormal distribution
- Cauchy distribution
Related to Bernoulli trials (yes/no events, with a given probability):
- Binomial distribution
- Geometric distribution
- Hypergeometric distribution
Related to positive real-valued quantities that grow exponentially (e.g. prices, incomes, populations):
- LogNormal distribution
Related to the occurrence of independent events at a given rate:
- Pareto distribution
- Poisson distribution
- Exponential distribution, and Exp1 as a primitive
- Weibull distribution
- Gumbel distribution
- Frechet distribution
- Zeta distribution
- Zipf distribution
Gamma and derived distributions:
- Gamma distribution
- ChiSquared distribution
- StudentT distribution
- FisherF distribution
Triangular distribution:
- Beta distribution
- Triangular distribution
Multivariate probability distributions
- Dirichlet distribution
- UnitSphere distribution
- UnitBall distribution
- UnitCircle distribution
- UnitDisc distribution
Alternative implementation for weighted index sampling
- WeightedAliasIndex distribution
Misc. distributions
- InverseGaussian distribution
- NormalInverseGaussian distribution

Re-exports

pub use weighted_alias::WeightedAliasIndex;

pub use num_traits;

Modules

uniform

A distribution uniformly sampling numbers within a given range.

weighted_alias

This module contains an implementation of alias method for sampling random indices with probabilities proportional to a collection of weights.

Structs

Alphanumeric

Sample a u8, uniformly distributed over ASCII letters and numbers: a-z, A-Z and 0-9.

Bernoulli

The Bernoulli distribution.

Beta

The Beta distribution with shape parameters alpha and beta.

Binomial

The binomial distribution Binomial(n, p).

Cauchy

The Cauchy distribution Cauchy(median, scale).

ChiSquared

The chi-squared distribution χ²(k), where k is the degrees of freedom.

Dirichlet

The Dirichlet distribution Dirichlet(alpha).

DistIter

An iterator that generates random values of T with distribution D, using R as the source of randomness.

Exp

The exponential distribution Exp(lambda).

Exp1

Samples floating-point numbers according to the exponential distribution, with rate parameter λ = 1. This is equivalent to Exp::new(1.0) or sampling with -rng.gen::<f64>().ln(), but faster.

FisherF

The Fisher F distribution F(m, n).

Frechet

Samples floating-point numbers according to the Fréchet distribution

Gamma

The Gamma distribution Gamma(shape, scale) distribution.

Geometric

The geometric distribution Geometric(p) bounded to [0, u64::MAX].

Gumbel

Samples floating-point numbers according to the Gumbel distribution

Hypergeometric

The hypergeometric distribution Hypergeometric(N, K, n).

InverseGaussian

The inverse Gaussian distribution

LogNormal

The log-normal distribution ln N(mean, std_dev**2).

Normal

The normal distribution N(mean, std_dev**2).

NormalInverseGaussian

The normal-inverse Gaussian distribution

Open01

A distribution to sample floating point numbers uniformly in the open interval (0, 1), i.e. not including either endpoint.

OpenClosed01

A distribution to sample floating point numbers uniformly in the half-open interval (0, 1], i.e. including 1 but not 0.

Pareto

Samples floating-point numbers according to the Pareto distribution

Pert

The PERT distribution.

Poisson

The Poisson distribution Poisson(lambda).

SkewNormal

The skew normal distribution SN(location, scale, shape).

Standard

A generic random value distribution, implemented for many primitive types. Usually generates values with a numerically uniform distribution, and with a range appropriate to the type.

StandardGeometric

Samples integers according to the geometric distribution with success probability p = 0.5. This is equivalent to Geometeric::new(0.5), but faster.

StandardNormal

Samples floating-point numbers according to the normal distribution N(0, 1) (a.k.a. a standard normal, or Gaussian). This is equivalent to Normal::new(0.0, 1.0) but faster.

StudentT

The Student t distribution, t(nu), where nu is the degrees of freedom.

Triangular

The triangular distribution.

Uniform

Sample values uniformly between two bounds.

UnitBall

Samples uniformly from the unit ball (surface and interior) in three dimensions.

UnitCircle

Samples uniformly from the edge of the unit circle in two dimensions.

UnitDisc

Samples uniformly from the unit disc in two dimensions.