Struct Gamma 

pub struct Gamma { /* private fields */ }

A continuous distribution over positive real numbers, parameterized by shape and rate.

Commonly used for modeling waiting times and as a conjugate prior for Poisson distributions.

Mathematical Properties:

• Support: (0, +∞)
• PDF: f(x) = (λ^k / Γ(k)) × x^(k-1) × exp(-λx)
• Mean: k / λ
• Variance: k / λ²

Example:

// Shape=1 gives Exponential distribution
let exponential_like = sample(addr!("wait_time"), Gamma::new(1.0, 2.0).unwrap());

// Prior for precision parameter
let precision = sample(addr!("precision"), Gamma::new(2.0, 1.0).unwrap());

// Conjugate prior for Poisson rate
let model = sample(addr!("rate"), Gamma::new(3.0, 2.0).unwrap())
    .bind(|lambda| observe(addr!("count"), Poisson::new(lambda).unwrap(), 5u64));

// Scale parameter (rate = 1/scale)
let scale_param = sample(addr!("scale"), Gamma::new(2.0, 0.5).unwrap()); // mean = 4

Implementations

impl Gamma

pub fn new(shape: f64, rate: f64) -> FugueResult<Self>

Create a new Gamma distribution with validated parameters.

pub fn shape(&self) -> f64

Get the shape parameter.

pub fn rate(&self) -> f64

Get the rate parameter.

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 Debug for Gamma

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

Formats the value using the given formatter.

impl Distribution<f64> for Gamma

fn sample(&self, rng: &mut dyn RngCore) -> f64

Generate a random sample (with its natural type), T, from the distribution, using the provided random number generator, rng.

fn log_prob(&self, x: &f64) -> LogF64

Compute the log-probability density (continuous) or mass (discrete) of a value, x, from the distribution.

fn clone_box(&self) -> Box<dyn Distribution<f64>>

Clone the distribution into a boxed trait object, Box<dyn Distribution<T>>.

impl Validate for Gamma

fn validate(&self) -> FugueResult<()>

impl Copy for Gamma