Struct std::rand::distributions::GammaUnstable
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[src]
pub struct Gamma {
// some fields omitted
}The Gamma distribution Gamma(shape, scale) distribution.
The density function of this distribution is
f(x) = x^(k - 1) * exp(-x / θ) / (Γ(k) * θ^k)
where Γ is the Gamma function, k is the shape and θ is the
scale and both k and θ are strictly positive.
The algorithm used is that described by Marsaglia & Tsang 2000[1],
falling back to directly sampling from an Exponential for shape
== 1, and using the boosting technique described in [1] for
shape < 1.
Example
fn main() { use std::rand; use std::rand::distributions::{IndependentSample, Gamma}; let gamma = Gamma::new(2.0, 5.0); let v = gamma.ind_sample(&mut rand::thread_rng()); println!("{} is from a Gamma(2, 5) distribution", v); }use std::rand; use std::rand::distributions::{IndependentSample, Gamma}; let gamma = Gamma::new(2.0, 5.0); let v = gamma.ind_sample(&mut rand::thread_rng()); println!("{} is from a Gamma(2, 5) distribution", v);
[1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method for Generating Gamma Variables" ACM Trans. Math. Softw. 26, 3 (September 2000), 363-372. DOI:10.1145/358407.358414
Methods
impl Gamma
fn new(shape: f64, scale: f64) -> Gamma
Construct an object representing the Gamma(shape, scale)
distribution.
Panics if shape <= 0 or scale <= 0.