Struct statrs::distribution::Bernoulli
source · [−]pub struct Bernoulli { /* private fields */ }
Expand description
Implements the
Bernoulli
distribution which is a special case of the
Binomial
distribution where n = 1
(referenced Here)
Examples
use statrs::distribution::{Bernoulli, Discrete};
use statrs::statistics::Distribution;
let n = Bernoulli::new(0.5).unwrap();
assert_eq!(n.mean().unwrap(), 0.5);
assert_eq!(n.pmf(0), 0.5);
assert_eq!(n.pmf(1), 0.5);
Implementations
sourceimpl Bernoulli
impl Bernoulli
sourcepub fn new(p: f64) -> Result<Bernoulli>
pub fn new(p: f64) -> Result<Bernoulli>
Constructs a new bernoulli distribution with
the given p
probability of success.
Errors
Returns an error if p
is NaN
, less than 0.0
or greater than 1.0
Examples
use statrs::distribution::Bernoulli;
let mut result = Bernoulli::new(0.5);
assert!(result.is_ok());
result = Bernoulli::new(-0.5);
assert!(result.is_err());
Trait Implementations
sourceimpl Discrete<u64, f64> for Bernoulli
impl Discrete<u64, f64> for Bernoulli
sourceimpl DiscreteCDF<u64, f64> for Bernoulli
impl DiscreteCDF<u64, f64> for Bernoulli
sourcefn cdf(&self, x: u64) -> f64
fn cdf(&self, x: u64) -> f64
Calculates the cumulative distribution
function for the bernoulli distribution at x
.
Formula
if x < 0 { 0 }
else if x >= 1 { 1 }
else { 1 - p }
sourcefn inverse_cdf(&self, p: T) -> K
fn inverse_cdf(&self, p: T) -> K
Due to issues with rounding and floating-point accuracy the default implementation may be ill-behaved Specialized inverse cdfs should be used whenever possible. Read more
sourceimpl Distribution<f64> for Bernoulli
impl Distribution<f64> for Bernoulli
sourcefn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64
Generate a random value of T
, using rng
as the source of randomness.
sourcefn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
R: Rng,
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. Read more
sourceimpl Distribution<f64> for Bernoulli
impl Distribution<f64> for Bernoulli
impl Copy for Bernoulli
impl StructuralPartialEq for Bernoulli
Auto Trait Implementations
impl RefUnwindSafe for Bernoulli
impl Send for Bernoulli
impl Sync for Bernoulli
impl Unpin for Bernoulli
impl UnwindSafe for Bernoulli
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcepub fn borrow_mut(&mut self) -> &mut T
pub fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
sourceimpl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
sourcepub fn to_subset(&self) -> Option<SS>
pub fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct self
from the equivalent element of its
superset. Read more
sourcepub fn is_in_subset(&self) -> bool
pub fn is_in_subset(&self) -> bool
Checks if self
is actually part of its subset T
(and can be converted to it).
sourcepub fn to_subset_unchecked(&self) -> SS
pub fn to_subset_unchecked(&self) -> SS
Use with care! Same as self.to_subset
but without any property checks. Always succeeds.
sourcepub fn from_subset(element: &SS) -> SP
pub fn from_subset(element: &SS) -> SP
The inclusion map: converts self
to the equivalent element of its superset.
sourceimpl<T> ToOwned for T where
T: Clone,
impl<T> ToOwned for T where
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
sourcepub fn to_owned(&self) -> T
pub fn to_owned(&self) -> T
Creates owned data from borrowed data, usually by cloning. Read more
sourcepub fn clone_into(&self, target: &mut T)
pub fn clone_into(&self, target: &mut T)
toowned_clone_into
)Uses borrowed data to replace owned data, usually by cloning. Read more