# Struct rand_distr::Hypergeometric

source · [−]`pub struct Hypergeometric { /* private fields */ }`

## Expand description

The hypergeometric distribution `Hypergeometric(N, K, n)`

.

This is the distribution of successes in samples of size `n`

drawn without
replacement from a population of size `N`

containing `K`

success states.
It has the density function:
`f(k) = binomial(K, k) * binomial(N-K, n-k) / binomial(N, n)`

,
where `binomial(a, b) = a! / (b! * (a - b)!)`

.

The binomial distribution is the analogous distribution for sampling with replacement. It is a good approximation when the population size is much larger than the sample size.

## Example

```
use rand_distr::{Distribution, Hypergeometric};
let hypergeo = Hypergeometric::new(60, 24, 7).unwrap();
let v = hypergeo.sample(&mut rand::thread_rng());
println!("{} is from a hypergeometric distribution", v);
```

## Implementations

## Trait Implementations

source### impl Clone for Hypergeometric

### impl Clone for Hypergeometric

source#### fn clone(&self) -> Hypergeometric

#### fn clone(&self) -> Hypergeometric

Returns a copy of the value. Read more

1.0.0 · source#### fn clone_from(&mut self, source: &Self)

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

Performs copy-assignment from `source`

. Read more

source### impl Debug for Hypergeometric

### impl Debug for Hypergeometric

source### impl Distribution<u64> for Hypergeometric

### impl Distribution<u64> for Hypergeometric

source#### fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64

#### fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64

Generate a random value of `T`

, using `rng`

as the source of randomness.

source#### 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,

#### 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 more

source### impl PartialEq<Hypergeometric> for Hypergeometric

### impl PartialEq<Hypergeometric> for Hypergeometric

source#### fn eq(&self, other: &Hypergeometric) -> bool

#### fn eq(&self, other: &Hypergeometric) -> bool

This method tests for `self`

and `other`

values to be equal, and is used
by `==`

. Read more

source#### fn ne(&self, other: &Hypergeometric) -> bool

#### fn ne(&self, other: &Hypergeometric) -> bool

This method tests for `!=`

.

### impl Copy for Hypergeometric

### impl StructuralPartialEq for Hypergeometric

## Auto Trait Implementations

### impl RefUnwindSafe for Hypergeometric

### impl Send for Hypergeometric

### impl Sync for Hypergeometric

### impl Unpin for Hypergeometric

### impl UnwindSafe for Hypergeometric

## Blanket Implementations

source### impl<T> BorrowMut<T> for T where

T: ?Sized,

### impl<T> BorrowMut<T> for T where

T: ?Sized,

const: unstable · source#### fn borrow_mut(&mut self) -> &mut T

#### fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more