Struct rand_distr::FisherF
source · [−]pub struct FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,{ /* private fields */ }
Expand description
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)
Implementations
sourceimpl<F> FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
impl<F> FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
sourcepub fn new(m: F, n: F) -> Result<FisherF<F>, FisherFError>
pub fn new(m: F, n: F) -> Result<FisherF<F>, FisherFError>
Create a new FisherF
distribution, with the given parameter.
Trait Implementations
sourceimpl<F: Clone> Clone for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
impl<F: Clone> Clone for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
sourceimpl<F: Debug> Debug for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
impl<F: Debug> Debug for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
sourceimpl<F> Distribution<F> for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
impl<F> Distribution<F> for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
sourcefn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> F
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> F
Generate a random value of
T
, using rng
as the source of randomness.sourcefn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>ⓘNotable 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;
where
R: Rng,
fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>ⓘNotable 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;
where
R: Rng,
D: Distribution<T>,
R: Rng, type Item = T;
Create an iterator that generates random values of
T
, using rng
as
the source of randomness. Read moreimpl<F: Copy> Copy for FisherF<F>where
F: Float,
StandardNormal: Distribution<F>,
Exp1: Distribution<F>,
Open01: Distribution<F>,
Auto Trait Implementations
impl<F> RefUnwindSafe for FisherF<F>where
F: RefUnwindSafe,
impl<F> Send for FisherF<F>where
F: Send,
impl<F> Sync for FisherF<F>where
F: Sync,
impl<F> Unpin for FisherF<F>where
F: Unpin,
impl<F> UnwindSafe for FisherF<F>where
F: UnwindSafe,
Blanket Implementations
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
const: unstablefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
impl<T> ToOwned for Twhere
T: Clone,
impl<T> ToOwned for Twhere
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
fn clone_into(&self, target: &mut T)
fn clone_into(&self, target: &mut T)
Uses borrowed data to replace owned data, usually by cloning. Read more