Struct ndarray_rand::rand_distr::Beta

pub struct Beta<N> { /* fields omitted */ }

The Beta distribution with shape parameters alpha and beta.

Example

use rand_distr::{Distribution, Beta};

let beta = Beta::new(2.0, 5.0).unwrap();
let v = beta.sample(&mut rand::thread_rng());
println!("{} is from a Beta(2, 5) distribution", v);

Methods

impl<N> Beta<N> where
    N: Float,
    StandardNormal: Distribution<N>,
    Exp1: Distribution<N>,
    Open01: Distribution<N>, 

pub fn new(alpha: N, beta: N) -> Result<Beta<N>, BetaError>

Construct an object representing the Beta(alpha, beta) distribution.

Trait Implementations

impl<N> Debug for Beta<N> where
    N: Debug, 

fn fmt(&self, f: &mut Formatter) -> Result<(), Error>

Formats the value using the given formatter.

impl<N> Copy for Beta<N> where
    N: Copy, 

impl<N> Clone for Beta<N> where
    N: Clone, 

fn clone(&self) -> Beta<N>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<N> Distribution<N> for Beta<N> where
    N: Float,
    StandardNormal: Distribution<N>,
    Exp1: Distribution<N>,
    Open01: Distribution<N>, 

fn sample<R>(&self, rng: &mut R) -> N where
    R: Rng + ?Sized, 

Generate a random value of T, using rng as the source of randomness.

Important traits for DistIter<D, R, T>

impl<D, R, T> Iterator for DistIter<D, R, T> where
    D: Distribution<T>,
    R: Rng,  type Item = T;

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
    R: Rng, 

Create an iterator that generates random values of T, using rng as the source of randomness.