Struct statrs::distribution::NegativeBinomial [−][src]
pub struct NegativeBinomial { /* fields omitted */ }
Expand description
Implements the NegativeBinomial distribution
Examples
use statrs::distribution::{NegativeBinomial, Discrete}; use statrs::statistics::DiscreteDistribution; use statrs::prec::almost_eq; let r = NegativeBinomial::new(4.0, 0.5).unwrap(); assert_eq!(r.mean().unwrap(), 4.0); assert!(almost_eq(r.pmf(0), 0.0625, 1e-8)); assert!(almost_eq(r.pmf(3), 0.15625, 1e-8));
Implementations
impl NegativeBinomial
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impl NegativeBinomial
[src]pub fn new(r: f64, p: f64) -> Result<NegativeBinomial>
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pub fn new(r: f64, p: f64) -> Result<NegativeBinomial>
[src]Constructs a new negative binomial distribution
with a given p
probability of the number of successes r
Errors
Returns an error if p
is NaN
, less than 0.0
,
greater than 1.0
, or if r
is NaN
or less than 0
Examples
use statrs::distribution::NegativeBinomial; let mut result = NegativeBinomial::new(4.0, 0.5); assert!(result.is_ok()); result = NegativeBinomial::new(-0.5, 5.0); assert!(result.is_err());
Trait Implementations
impl Clone for NegativeBinomial
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impl Clone for NegativeBinomial
[src]fn clone(&self) -> NegativeBinomial
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fn clone(&self) -> NegativeBinomial
[src]Returns a copy of the value. Read more
fn clone_from(&mut self, source: &Self)
1.0.0[src]
fn clone_from(&mut self, source: &Self)
1.0.0[src]Performs copy-assignment from source
. Read more
impl Debug for NegativeBinomial
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impl Debug for NegativeBinomial
[src]impl Discrete<u64, f64> for NegativeBinomial
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impl Discrete<u64, f64> for NegativeBinomial
[src]impl DiscreteCDF<u64, f64> for NegativeBinomial
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impl DiscreteCDF<u64, f64> for NegativeBinomial
[src]fn cdf(&self, x: u64) -> f64
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fn cdf(&self, x: u64) -> f64
[src]Calculates the cumulative distribution function for the
negative binomial distribution at x
Note that due to extending the distribution to the reals
(allowing positive real values for r
), while still technically
a discrete distribution the CDF behaves more like that of a
continuous distribution rather than a discrete distribution
(i.e. a smooth graph rather than a step-ladder)
Formula
1 - I_(1 - p)(x + 1, r)
where I_(x)(a, b)
is the regularized incomplete beta function
fn inverse_cdf(&self, p: T) -> K
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fn inverse_cdf(&self, p: T) -> K
[src]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
impl DiscreteDistribution<f64> for NegativeBinomial
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impl DiscreteDistribution<f64> for NegativeBinomial
[src]impl Distribution<u64> for NegativeBinomial
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impl Distribution<u64> for NegativeBinomial
[src]fn sample<R: Rng + ?Sized>(&self, r: &mut R) -> u64
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fn sample<R: Rng + ?Sized>(&self, r: &mut R) -> u64
[src]Generate a random value of T
, using rng
as the source of randomness.
fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
R: Rng,
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fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
R: Rng,
[src]Create an iterator that generates random values of T
, using rng
as
the source of randomness. Read more
impl Max<u64> for NegativeBinomial
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impl Max<u64> for NegativeBinomial
[src]impl Min<u64> for NegativeBinomial
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impl Min<u64> for NegativeBinomial
[src]impl Mode<Option<f64>> for NegativeBinomial
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impl Mode<Option<f64>> for NegativeBinomial
[src]impl PartialEq<NegativeBinomial> for NegativeBinomial
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impl PartialEq<NegativeBinomial> for NegativeBinomial
[src]fn eq(&self, other: &NegativeBinomial) -> bool
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fn eq(&self, other: &NegativeBinomial) -> bool
[src]This method tests for self
and other
values to be equal, and is used
by ==
. Read more
fn ne(&self, other: &NegativeBinomial) -> bool
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fn ne(&self, other: &NegativeBinomial) -> bool
[src]This method tests for !=
.
impl Copy for NegativeBinomial
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impl StructuralPartialEq for NegativeBinomial
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Auto Trait Implementations
impl RefUnwindSafe for NegativeBinomial
impl Send for NegativeBinomial
impl Sync for NegativeBinomial
impl Unpin for NegativeBinomial
impl UnwindSafe for NegativeBinomial
Blanket Implementations
impl<T> BorrowMut<T> for T where
T: ?Sized,
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impl<T> BorrowMut<T> for T where
T: ?Sized,
[src]pub fn borrow_mut(&mut self) -> &mut T
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pub fn borrow_mut(&mut self) -> &mut T
[src]Mutably borrows from an owned value. Read more
impl<T> Same<T> for T
impl<T> Same<T> for T
type Output = T
type Output = T
Should always be Self
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
pub 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
pub 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).
pub 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.
pub 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.
impl<T> ToOwned for T where
T: Clone,
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impl<T> ToOwned for T where
T: Clone,
[src]type Owned = T
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn to_owned(&self) -> T
[src]Creates owned data from borrowed data, usually by cloning. Read more
pub fn clone_into(&self, target: &mut T)
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pub fn clone_into(&self, target: &mut T)
[src]🔬 This is a nightly-only experimental API. (toowned_clone_into
)
recently added
Uses borrowed data to replace owned data, usually by cloning. Read more
impl<V, T> VZip<V> for T where
V: MultiLane<T>,
impl<V, T> VZip<V> for T where
V: MultiLane<T>,