Struct statrs::distribution::Weibull [−][src]
pub struct Weibull { /* fields omitted */ }
Expand description
Implements the Weibull distribution
Examples
use statrs::distribution::{Weibull, Continuous}; use statrs::statistics::Distribution; use statrs::prec; let n = Weibull::new(10.0, 1.0).unwrap(); assert!(prec::almost_eq(n.mean().unwrap(), 0.95135076986687318362924871772654021925505786260884, 1e-15)); assert_eq!(n.pdf(1.0), 3.6787944117144232159552377016146086744581113103177);
Implementations
Constructs a new weibull distribution with a shape (k) of shape
and a scale (λ) of scale
Errors
Returns an error if shape
or scale
are NaN
.
Returns an error if shape <= 0.0
or scale <= 0.0
Examples
use statrs::distribution::Weibull; let mut result = Weibull::new(10.0, 1.0); assert!(result.is_ok()); result = Weibull::new(0.0, 0.0); assert!(result.is_err());
Returns the shape of the weibull distribution
Examples
use statrs::distribution::Weibull; let n = Weibull::new(10.0, 1.0).unwrap(); assert_eq!(n.shape(), 10.0);
Trait Implementations
Calculates the probability density function for the weibull
distribution at x
Formula
(k / λ) * (x / λ)^(k - 1) * e^(-(x / λ)^k)
where k
is the shape and λ
is the scale
Calculates the cumulative distribution function for the weibull
distribution at x
Formula
1 - e^-((x/λ)^k)
where k
is the shape and λ
is the scale
Due to issues with rounding and floating-point accuracy the default
implementation may be ill-behaved.
Specialized inverse cdfs should be used whenever possible.
Performs a binary search on the domain of cdf
to obtain an approximation
of F^-1(p) := inf { x | F(x) >= p }
. Needless to say, performance may
may be lacking. Read more
Returns the mean of the weibull distribution
Formula
λΓ(1 + 1 / k)
where k
is the shape, λ
is the scale, and Γ
is
the gamma function
Returns the variance of the weibull distribution
Formula
λ^2 * (Γ(1 + 2 / k) - Γ(1 + 1 / k)^2)
where k
is the shape, λ
is the scale, and Γ
is
the gamma function
Returns the entropy of the weibull distribution
Formula
γ(1 - 1 / k) + ln(λ / k) + 1
where k
is the shape, λ
is the scale, and γ
is
the Euler-Mascheroni constant
Returns the skewness of the weibull distribution
Formula
(Γ(1 + 3 / k) * λ^3 - 3μσ^2 - μ^3) / σ^3
where k
is the shape, λ
is the scale, and Γ
is
the gamma function, μ
is the mean of the distribution.
and σ
the standard deviation of the distribution
Generate a random value of T
, using rng
as the source of randomness.
Create an iterator that generates random values of T
, using rng
as
the source of randomness. Read more
Auto Trait Implementations
impl RefUnwindSafe for Weibull
impl UnwindSafe for Weibull
Blanket Implementations
Mutably borrows from an owned value. Read more
type Output = T
type Output = T
Should always be Self
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.
pub fn vzip(self) -> V