Crate rand_distr

Generating random samples from probability distributions.

Re-exports

This crate is a super-set of the rand::distr module. See the rand::distr 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 implementations for weighted index sampling
  • WeightedAliasIndex distribution
  • WeightedTreeIndex distribution
• Misc. distributions
  • InverseGaussian distribution
  • NormalInverseGaussian distribution

Re-exports

• pub use weighted_alias::WeightedAliasIndex;
• pub use weighted_tree::WeightedTreeIndex;
• 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.
• weighted_tree
  This module contains an implementation of a tree structure 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 Bernoulli(p).
• Beta
  The Beta distribution Beta(α, β).
• Binomial
  The binomial distribution Binomial(n, p).
• Cauchy
  The Cauchy distribution Cauchy(x₀, γ).
• ChiSquared
  The chi-squared distribution χ²(k).
• Dirichlet
  The Dirichlet distribution Dirichlet(α₁, α₂, ..., αₖ).
• DistIter
  An iterator that generates random values of T with distribution D, using R as the source of randomness.
• Exp
  The exponential distribution Exp(λ).
• Exp1
  The standard exponential distribution Exp(1).
• FisherF
  The Fisher F-distribution F(m, n).
• Frechet
  The Fréchet distribution Fréchet(α, μ, σ).
• Gamma
  The Gamma distribution Gamma(k, θ).
• Geometric
  The geometric distribution Geometric(p).
• Gumbel
  The Gumbel distribution Gumbel(μ, β).
• Hypergeometric
  The hypergeometric distribution Hypergeometric(N, K, n).
• InverseGaussian
  The inverse Gaussian distribution IG(μ, λ).
• LogNormal
  The log-normal distribution ln N(μ, σ²).
• Normal
  The Normal distribution N(μ, σ²).
• NormalInverseGaussian
  The normal-inverse Gaussian distribution NIG(α, β).
• 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
  The Pareto distribution Pareto(xₘ, α).
• Pert
  The PERT distribution PERT(min, max, mode, shape).
• PertBuilder
  Struct used to build a Pert
• Poisson
  The Poisson distribution Poisson(λ).
• SkewNormal
  The skew normal distribution SN(ξ, ω, α).
• 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
  The standard geometric distribution Geometric(0.5).
• StandardNormal
  The standard Normal distribution N(0, 1).
• StudentT
  The Student t-distribution t(ν).
• Triangular
  The triangular distribution Triangular(min, max, mode).
• Uniform
  Sample values uniformly between two bounds.
• UnitBall
  Samples uniformly from the volume of the unit ball in three dimensions.
• UnitCircle
  Samples uniformly from the circumference of the unit circle in two dimensions.
• UnitDisc
  Samples uniformly from the unit disc in two dimensions.
• UnitSphere
  Samples uniformly from the surface of the unit sphere in three dimensions.
• Weibull
  The Weibull distribution Weibull(λ, k).
• WeightedIndex
  A distribution using weighted sampling of discrete items.
• Zeta
  The Zeta distribution Zeta(s).
• Zipf
  The Zipf (Zipfian) distribution Zipf(n, s).

Enums

• BernoulliError
  Error type returned from Bernoulli::new.
• BetaError
  Error type returned from Beta::new.
• BinomialError
  Error type returned from Binomial::new.
• CauchyError
  Error type returned from Cauchy::new.
• ChiSquaredError
  Error type returned from ChiSquared::new and StudentT::new.
• DirichletError
  Error type returned from Dirichlet::new.
• ExpError
  Error type returned from Exp::new.
• FisherFError
  Error type returned from FisherF::new.
• FrechetError
  Error type returned from Frechet::new.
• GammaError
  Error type returned from Gamma::new.
• GeoError
  Error type returned from Geometric::new.
• GumbelError
  Error type returned from Gumbel::new.
• HyperGeoError
  Error type returned from Hypergeometric::new.
• InverseGaussianError
  Error type returned from InverseGaussian::new
• NormalError
  Error type returned from Normal::new and LogNormal::new.
• NormalInverseGaussianError
  Error type returned from NormalInverseGaussian::new
• ParetoError
  Error type returned from Pareto::new.
• PertError
  Error type returned from Pert constructors.
• PoissonError
  Error type returned from Poisson::new.
• SkewNormalError
  Error type returned from SkewNormal::new.
• TriangularError
  Error type returned from Triangular::new.
• WeibullError
  Error type returned from Weibull::new.
• WeightError
  Errors returned by WeightedIndex::new, WeightedIndex::update_weights and other weighted distributions
• ZetaError
  Error type returned from Zeta::new.
• ZipfError
  Error type returned from Zipf::new.

Traits

• Distribution
  Types (distributions) that can be used to create a random instance of T.