Struct Gamma 

pub struct Gamma { /* private fields */ }

Implements the Gamma distribution

Examples

use statrs::distribution::{Gamma, Continuous};
use statrs::statistics::Distribution;
use statrs::prec;

let n = Gamma::new(3.0, 1.0).unwrap();
assert_eq!(n.mean().unwrap(), 3.0);
assert!(prec::almost_eq(n.pdf(2.0), 0.270670566473225383788, 1e-15));

Implementations

impl Gamma

pub fn new(shape: f64, rate: f64) -> Result<Gamma, GammaError>

Constructs a new gamma distribution with a shape (α) of shape and a rate (β) of rate

Errors

Returns an error if shape is ‘NaN’ or inf or rate is NaN or inf. Also returns an error if shape <= 0.0 or rate <= 0.0

Examples

use statrs::distribution::Gamma;

let mut result = Gamma::new(3.0, 1.0);
assert!(result.is_ok());

result = Gamma::new(0.0, 0.0);
assert!(result.is_err());

pub fn shape(&self) -> f64

Returns the shape (α) of the gamma distribution

Examples

use statrs::distribution::Gamma;

let n = Gamma::new(3.0, 1.0).unwrap();
assert_eq!(n.shape(), 3.0);

pub fn rate(&self) -> f64

Returns the rate (β) of the gamma distribution

Examples

use statrs::distribution::Gamma;

let n = Gamma::new(3.0, 1.0).unwrap();
assert_eq!(n.rate(), 1.0);

Trait Implementations

impl Clone for Gamma

fn clone(&self) -> Gamma

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Continuous<f64, f64> for Gamma

fn pdf(&self, x: f64) -> f64

Calculates the probability density function for the gamma distribution at x

Remarks

Returns NAN if any of shape or rate are f64::INFINITY or if x is f64::INFINITY

Formula

(β^α / Γ(α)) * x^(α - 1) * e^(-β * x)

where α is the shape, β is the rate, and Γ is the gamma function

fn ln_pdf(&self, x: f64) -> f64

Calculates the log probability density function for the gamma distribution at x

Remarks

Returns NAN if any of shape or rate are f64::INFINITY or if x is f64::INFINITY

Formula

ln((β^α / Γ(α)) * x^(α - 1) * e ^(-β * x))

where α is the shape, β is the rate, and Γ is the gamma function

impl ContinuousCDF<f64, f64> for Gamma

fn cdf(&self, x: f64) -> f64

Calculates the cumulative distribution function for the gamma distribution at x

Formula

(1 / Γ(α)) * γ(α, β * x)

where α is the shape, β is the rate, Γ is the gamma function, and γ is the lower incomplete gamma function

fn sf(&self, x: f64) -> f64

Calculates the survival function for the gamma distribution at x

Formula

(1 / Γ(α)) * γ(α, β * x)

where α is the shape, β is the rate, Γ is the gamma function, and γ is the upper incomplete gamma function

fn inverse_cdf(&self, p: f64) -> f64

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.

impl Debug for Gamma

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Display for Gamma

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Distribution<f64> for Gamma

Available on crate feature rand only.

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64

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, Self: Sized,

Create an iterator that generates random values of T, using rng as the source of randomness.

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>

where F: Fn(T) -> S, Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

impl Distribution<f64> for Gamma

fn mean(&self) -> Option<f64>

Returns the mean of the gamma distribution

Formula

α / β

where α is the shape and β is the rate

fn variance(&self) -> Option<f64>

Returns the variance of the gamma distribution

Formula

α / β^2

where α is the shape and β is the rate

fn entropy(&self) -> Option<f64>

Returns the entropy of the gamma distribution

Formula

α - ln(β) + ln(Γ(α)) + (1 - α) * ψ(α)

where α is the shape, β is the rate, Γ is the gamma function, and ψ is the digamma function

fn skewness(&self) -> Option<f64>

Returns the skewness of the gamma distribution

Formula

2 / sqrt(α)

where α is the shape

fn std_dev(&self) -> Option<T>

Returns the standard deviation, if it exists.

impl Max<f64> for Gamma

fn max(&self) -> f64

Returns the maximum value in the domain of the gamma distribution representable by a double precision float

Formula

f64::INFINITY

impl Min<f64> for Gamma

fn min(&self) -> f64

Returns the minimum value in the domain of the gamma distribution representable by a double precision float

Formula

0

impl Mode<Option<f64>> for Gamma

fn mode(&self) -> Option<f64>

Returns the mode for the gamma distribution

Formula

(α - 1) / β, where α≥1

where α is the shape and β is the rate

impl PartialEq for Gamma

fn eq(&self, other: &Gamma) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for Gamma

impl StructuralPartialEq for Gamma