Module statrs::distribution [−] [src]

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
Chi	Implements the Chi distribution
ChiSquared	Implements the Chi-squared distribution which is a special case of the Gamma distribution (referenced Here)
DiscreteUniform	Implements the Discrete Uniform distribution
Exponential	Implements the Exponential distribution and is a special case of the Gamma distribution (referenced here)
Gamma	Implements the Gamma distribution
LogNormal	Implements the Log-normal distribution
Normal	Implements the Normal 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

Continuous	The `Continuous` trait extends the `Distribution` trait and provides an interface for interacting with continuous statistical distributions
Discrete	The `Discrete` trait extends the `Distribution` trait and provides an interface for interacting with discrete statistical distributions
Distribution	The `Distribution` trait is used to specify an interface for sampling statistical distributions
Entropy	The `Entropy` trait specifies a distribution with a closed form solution for its entropy
Mean	The `Mean` trait specifies a distribution that has a closed form solution for its mean(s)
Median	The `Median` trait specifies a distribution with a closed form solution for its median
Mode	The `Mode` trait specififies a distribution with a closed form solution for its mode(s)
Skewness	The `Skewness` trait specifies a distributions with a closed form solution for its skewness(s)
Univariate	The `Univariate` trait is used to specify an interface for univariate distributions e.g. distributions that have a closed form cumulative distribution function
Variance	The `Variance` trait specifies a distribution that has a closed form solution for its variance(s). Requires `Mean` since a closed form solution to variance by definition requires a closed form mean.