Struct rand_distr::ChiSquared

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

The chi-squared distribution χ²(k), where k is the degrees of freedom.

For k > 0 integral, this distribution is the sum of the squares of k independent standard normal random variables. For other k, this uses the equivalent characterisation χ²(k) = Gamma(k/2, 2).

Example

use rand_distr::{ChiSquared, Distribution};

let chi = ChiSquared::new(11.0).unwrap();
let v = chi.sample(&mut rand::thread_rng());
println!("{} is from a χ²(11) distribution", v)

Methods

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

pub fn new(k: N) -> Result<ChiSquared<N>, ChiSquaredError>

Create a new chi-squared distribution with degrees-of-freedom k.

Trait Implementations

impl<N: Clone> Clone for ChiSquared<N>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N: Copy> Copy for ChiSquared<N>

impl<N: Debug> Debug for ChiSquared<N>

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

Formats the value using the given formatter.

impl<N: Float> Distribution<N> for ChiSquared<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.