Trait rv::traits::ContinuousDistr
source · pub trait ContinuousDistr<X>: HasDensity<X> + Support<X> {
// Provided methods
fn pdf(&self, x: &X) -> f64 { ... }
fn ln_pdf(&self, x: &X) -> f64 { ... }
}Expand description
Is a continuous probability distributions
This trait uses the Rv<X> and Support<X> implementations to implement
itself.
Provided Methods§
sourcefn pdf(&self, x: &X) -> f64
fn pdf(&self, x: &X) -> f64
The value of the Probability Density Function (PDF) at x
§Example
Compute the Gaussian PDF, f(x)
use rv::dist::Gaussian;
use rv::traits::ContinuousDistr;
let g = Gaussian::standard();
let f_mean = g.pdf(&0.0_f64);
let f_low = g.pdf(&-1.0_f64);
let f_high = g.pdf(&1.0_f64);
assert!(f_mean > f_low);
assert!(f_mean > f_high);
assert!((f_low - f_high).abs() < 1E-12);Returns 0 if x is not in support
use rv::dist::Exponential;
let expon = Exponential::new(1.0).unwrap();
let f = expon.pdf(&-1.0_f64);
assert_eq!(f, 0.0);sourcefn ln_pdf(&self, x: &X) -> f64
fn ln_pdf(&self, x: &X) -> f64
The value of the log Probability Density Function (PDF) at x
§Example
Compute the natural logarithm of the Gaussian PDF, ln(f(x))
use rv::dist::Gaussian;
use rv::traits::ContinuousDistr;
let g = Gaussian::standard();
let lnf_mean = g.ln_pdf(&0.0_f64);
let lnf_low = g.ln_pdf(&-1.0_f64);
let lnf_high = g.ln_pdf(&1.0_f64);
assert!(lnf_mean > lnf_low);
assert!(lnf_mean > lnf_high);
assert!((lnf_low - lnf_high).abs() < 1E-12);Returns -inf if x is not in support
use rv::dist::Exponential;
let expon = Exponential::new(1.0).unwrap();
let f = expon.ln_pdf(&-1.0_f64);
assert_eq!(f, f64::NEG_INFINITY);