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use random::Source;
pub trait Distribution {
type Value;
fn cdf(&self, f64) -> f64;
}
pub trait Continuous: Distribution {
fn pdf(&self, f64) -> f64;
}
pub trait Discrete: Distribution {
fn pmf(&self, Self::Value) -> f64;
}
pub trait Entropy: Distribution {
fn entropy(&self) -> f64;
}
pub trait Inverse: Distribution {
fn inv_cdf(&self, f64) -> Self::Value;
}
pub trait Kurtosis: Skewness {
fn kurtosis(&self) -> f64;
}
pub trait Mean: Distribution {
fn mean(&self) -> f64;
}
pub trait Median: Distribution {
fn median(&self) -> f64;
}
pub trait Modes: Distribution {
fn modes(&self) -> Vec<Self::Value>;
}
pub trait Sample: Distribution {
fn sample<S>(&self, &mut S) -> Self::Value where S: Source;
}
pub trait Skewness: Variance {
fn skewness(&self) -> f64;
}
pub trait Variance: Mean {
fn variance(&self) -> f64;
#[inline(always)]
fn deviation(&self) -> f64 {
self.variance().sqrt()
}
#[inline(always)]
fn var(&self) -> f64 {
self.variance()
}
#[inline(always)]
fn sd(&self) -> f64 {
self.deviation()
}
}
pub use self::bernoulli::Bernoulli;
pub use self::beta::Beta;
pub use self::binomial::Binomial;
pub use self::categorical::Categorical;
pub use self::exponential::Exponential;
pub use self::gamma::Gamma;
pub use self::gaussian::Gaussian;
pub use self::uniform::Uniform;
mod bernoulli;
mod beta;
mod binomial;
mod categorical;
mod exponential;
mod gamma;
mod gaussian;
mod uniform;