pub struct Weibull { /* fields omitted */ }Implements the Weibull
distribution
use statrs::distribution::{Weibull, Continuous};
use statrs::statistics::Mean;
use statrs::prec;
let n = Weibull::new(10.0, 1.0).unwrap();
assert!(prec::almost_eq(n.mean(),
0.95135076986687318362924871772654021925505786260884, 1e-15));
assert_eq!(n.pdf(1.0), 3.6787944117144232159552377016146086744581113103177);
Constructs a new weibull distribution with a shape (k) of shape
and a scale (λ) of scale
Returns an error if shape or scale are NaN.
Returns an error if shape <= 0.0 or scale <= 0.0
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
use statrs::distribution::Weibull;
let n = Weibull::new(10.0, 1.0).unwrap();
assert_eq!(n.shape(), 10.0);
Returns the scale of the weibull distribution
use statrs::distribution::Weibull;
let n = Weibull::new(10.0, 1.0).unwrap();
assert_eq!(n.scale(), 1.0);
Formats the value using the given formatter. Read more
Performs copy-assignment from source. Read more
This method tests for self and other values to be equal, and is used by ==. Read more
This method tests for !=.
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
Calculates the cumulative distribution function for the weibull
distribution at x
1 - e^-((x/λ)^k)
where k is the shape and λ is the scale
Returns the minimum value in the domain of the weibull
distribution representable by a double precision float
0
Returns the maximum value in the domain of the weibull
distribution representable by a double precision float
INF
Returns the mean of the weibull distribution
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
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 standard deviation of the weibull distribution
sqrt(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
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
(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
Returns the median of the weibull distribution
λ(ln(2))^(1 / k)
where k is the shape and λ is the scale
Returns the median of the weibull distribution
if k == 1 {
0
} else {
λ((k - 1) / k)^(1 / k)
}
where k is the shape and λ is the scale
Calculates the probability density function for the weibull
distribution at x
(k / λ) * (x / λ)^(k - 1) * e^(-(x / λ)^k)
where k is the shape and λ is the scale
Calculates the log probability density function for the weibull
distribution at x
ln((k / λ) * (x / λ)^(k - 1) * e^(-(x / λ)^k))
where k is the shape and λ is the scale