Trait Continuous

Source

pub trait Continuous<K, T> {
    // Required methods
    fn pdf(&self, x: K) -> T;
    fn ln_pdf(&self, x: K) -> T;
}

Expand description

The Continuous trait provides an interface for interacting with continuous statistical distributions

§Remarks

All methods provided by the Continuous trait are unchecked, meaning they can panic if in an invalid state or encountering invalid input depending on the implementing distribution.

Required Methods§

Source

fn pdf(&self, x: K) -> T

Returns the probability density function calculated at x for a given distribution. May panic depending on the implementor.

§Examples

use statrs::distribution::{Continuous, Uniform};

let n = Uniform::new(0.0, 1.0).unwrap();
assert_eq!(1.0, n.pdf(0.5));

Source

fn ln_pdf(&self, x: K) -> T

Returns the log of the probability density function calculated at x for a given distribution. May panic depending on the implementor.

§Examples

use statrs::distribution::{Continuous, Uniform};

let n = Uniform::new(0.0, 1.0).unwrap();
assert_eq!(0.0, n.ln_pdf(0.5));

Implementors§

Source §

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for Dirichlet<D>
where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D> + Allocator<Const<1>, D>,

Available on crate feature nalgebra only.

Source §

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for MultivariateNormal<D>
where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D>,

Available on crate feature nalgebra only.

Source §

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for MultivariateStudent<D>
where D: Dim + DimMin<D, Output = D>, DefaultAllocator: Allocator<D> + Allocator<D, D>,

Available on crate feature nalgebra only.

Continuous

Trait Continuous Copy item path

§Remarks

Required Methods§

fn pdf(&self, x: K) -> T

§Examples

fn ln_pdf(&self, x: K) -> T

§Examples

Implementors§

impl Continuous<f64, f64> for Beta

impl Continuous<f64, f64> for Cauchy

impl Continuous<f64, f64> for Chi

impl Continuous<f64, f64> for ChiSquared

impl Continuous<f64, f64> for Erlang

impl Continuous<f64, f64> for Exp

impl Continuous<f64, f64> for FisherSnedecor

impl Continuous<f64, f64> for Gamma

impl Continuous<f64, f64> for Gumbel

impl Continuous<f64, f64> for InverseGamma

impl Continuous<f64, f64> for Laplace

impl Continuous<f64, f64> for LogNormal

impl Continuous<f64, f64> for Normal

impl Continuous<f64, f64> for Pareto

impl Continuous<f64, f64> for StudentsT

impl Continuous<f64, f64> for Triangular

impl Continuous<f64, f64> for Uniform

impl Continuous<f64, f64> for Weibull

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for Dirichlet<D>where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D> + Allocator<Const<1>, D>,

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for MultivariateNormal<D>where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D>,

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for MultivariateStudent<D>where D: Dim + DimMin<D, Output = D>, DefaultAllocator: Allocator<D> + Allocator<D, D>,

Trait Continuous

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for Dirichlet<D>
where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D> + Allocator<Const<1>, D>,

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for MultivariateNormal<D>
where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D>,

impl<D> Continuous<&Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>, f64> for MultivariateStudent<D>
where D: Dim + DimMin<D, Output = D>, DefaultAllocator: Allocator<D> + Allocator<D, D>,