Struct ndarray_rand::rand_distr::Frechet

pub struct Frechet<F>
where
    F: Float,
    OpenClosed01: Distribution<F>,
{ /* private fields */ }

Samples floating-point numbers according to the Fréchet distribution

This distribution has density function: f(x) = [(x - μ) / σ]^(-1 - α) exp[-(x - μ) / σ]^(-α) α / σ, where μ is the location parameter, σ the scale parameter, and α the shape parameter.

Example

use rand::prelude::*;
use rand_distr::Frechet;

let val: f64 = thread_rng().sample(Frechet::new(0.0, 1.0, 1.0).unwrap());
println!("{}", val);

Implementations

impl<F> Frechet<F>

where F: Float, OpenClosed01: Distribution<F>,

pub fn new(location: F, scale: F, shape: F) -> Result<Frechet<F>, Error>

Construct a new Frechet distribution with given location, scale, and shape.

Trait Implementations

impl<F> Clone for Frechet<F>

where F: Clone + Float, OpenClosed01: Distribution<F>,

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F> Debug for Frechet<F>

where F: Debug + Float, OpenClosed01: Distribution<F>,

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

Formats the value using the given formatter.

impl<F> Distribution<F> for Frechet<F>

where F: Float, OpenClosed01: 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) -> DistIter<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) -> DistMap<Self, F, T, S>

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

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

impl<F> Copy for Frechet<F>

where F: Copy + Float, OpenClosed01: Distribution<F>,