Struct Beta

pub struct Beta<F>
where
    F: Float,
    Open01: Distribution<F>,
{ /* private fields */ }

The Beta distribution Beta(α, β).

The Beta distribution is a continuous probability distribution defined on the interval [0, 1]. It is the conjugate prior for the parameter p of the Binomial distribution.

It has two shape parameters α (alpha) and β (beta) which control the shape of the distribution. Both a and β must be greater than zero. The distribution is symmetric when α = β.

Plot

The plot shows the Beta distribution with various combinations of α and β.

Example

use rand_distr::{Distribution, Beta};

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

Implementations

impl<F> Beta<F>

where F: Float, Open01: Distribution<F>,

pub fn new(alpha: F, beta: F) -> Result<Beta<F>, Error>

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

Trait Implementations

impl<F> Clone for Beta<F>

where F: Clone + Float, Open01: Distribution<F>,

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F> Debug for Beta<F>

where F: Debug + Float, Open01: Distribution<F>,

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

Formats the value using the given formatter.

impl<'de, F> Deserialize<'de> for Beta<F>

where F: Float + Deserialize<'de>, Open01: Distribution<F>,

fn deserialize<__D>( __deserializer: __D, ) -> Result<Beta<F>, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<F> Distribution<F> for Beta<F>

where F: Float, Open01: Distribution<F>,

fn sample<R>(&self, rng: &mut R) -> F

where R: Rng + ?Sized,

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

fn sample_iter<R>(self, rng: R) -> Iter<Self, R, T>

where R: Rng, Self: Sized,

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

fn map<F, S>(self, func: F) -> Map<Self, F, T, S>

where F: Fn(T) -> S, Self: Sized,

Map sampled values to type S

impl<F> PartialEq for Beta<F>

where F: PartialEq + Float, Open01: Distribution<F>,

fn eq(&self, other: &Beta<F>) -> bool

Tests for self and other values to be equal, and is used by ==.

const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<F> Serialize for Beta<F>

where F: Float + Serialize, Open01: Distribution<F>,

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<F> Copy for Beta<F>

where F: Copy + Float, Open01: Distribution<F>,

impl<F> StructuralPartialEq for Beta<F>

where F: Float, Open01: Distribution<F>,