Struct ndarray_rand::rand_distr::ChiSquared

pub struct ChiSquared<F> where
    F: Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>,  { /* 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)

Implementations

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

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

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

Trait Implementations

impl<F> Clone for ChiSquared<F> where
    F: Clone + Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

pub fn clone(&self) -> ChiSquared<F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F> Copy for ChiSquared<F> where
    F: Copy + Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

impl<F> Debug for ChiSquared<F> where
    F: Debug + Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

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

Formats the value using the given formatter.

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

pub 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.

pub 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.