Struct rand_distr::FisherF

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

The Fisher F distribution F(m, n).

This distribution is equivalent to the ratio of two normalised chi-squared distributions, that is, F(m,n) = (χ²(m)/m) / (χ²(n)/n).

Example

use rand_distr::{FisherF, Distribution};

let f = FisherF::new(2.0, 32.0).unwrap();
let v = f.sample(&mut rand::thread_rng());
println!("{} is from an F(2, 32) distribution", v)

Methods

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

pub fn new(m: N, n: N) -> Result<FisherF<N>, FisherFError>

Create a new FisherF distribution, with the given parameter.

Trait Implementations

impl<N: Copy> Copy for FisherF<N>

impl<N: Clone> Clone for FisherF<N>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N: Debug> Debug for FisherF<N>

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

Formats the value using the given formatter.

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

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

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.