Module statrs::distribution

Defines common interfaces for interacting with statistical distributions and provides concrete implementations for a variety of distributions.

Structs

Bernoulli	Implements the Bernoulli distribution which is a special case of the Binomial distribution where n = 1 (referenced Here)
Beta	Implements the Beta distribution
Binomial	Implements the Binomial distribution
Categorical	Implements the Categorical distribution, also known as the generalized Bernoulli or discrete distribution
Cauchy	Implements the Cauchy distribution, also known as the Lorentz distribution.
Chi	Implements the Chi distribution
ChiSquared	Implements the Chi-squared distribution which is a special case of the Gamma distribution (referenced Here)
Dirac	Implements the Dirac Delta distribution
Dirichlet	Implements the Dirichlet distribution
DiscreteUniform	Implements the Discrete Uniform distribution
Empirical	Implements the Empirical Distribution
Erlang	Implements the Erlang distribution which is a special case of the Gamma distribution
Exp	Implements the Exp distribution and is a special case of the Gamma distribution (referenced here)
FisherSnedecor	Implements the Fisher-Snedecor distribution also commonly known as the F-distribution
Gamma	Implements the Gamma distribution
Geometric	Implements the Geometric distribution
Hypergeometric	Implements the Hypergeometric distribution
InverseGamma	Implements the Inverse Gamma distribution
Laplace	Implements the Laplace distribution.
LogNormal	Implements the Log-normal distribution
Multinomial	Implements the Multinomial distribution which is a generalization of the Binomial distribution
MultivariateNormal	Implements the Multivariate Normal distribution using the “nalgebra” crate for matrix operations
NegativeBinomial	Implements the NegativeBinomial distribution
Normal	Implements the Normal distribution
Pareto	Implements the Pareto distribution
Poisson	Implements the Poisson distribution
StudentsT	Implements the Student’s T distribution
Triangular	Implements the Triangular distribution
Uniform	Implements the Continuous Uniform distribution
Weibull	Implements the Weibull distribution

Traits

Continuous	The Continuous trait provides an interface for interacting with continuous statistical distributions
ContinuousCDF	The ContinuousCDF trait is used to specify an interface for univariate distributions for which cdf float arguments are sensible.
Discrete	The Discrete trait provides an interface for interacting with discrete statistical distributions
DiscreteCDF	The DiscreteCDF trait is used to specify an interface for univariate discrete distributions.