Struct mathru::statistics::distrib::Uniform

pub struct Uniform<T> { /* fields omitted */ }

Uniform distribution

Fore more information: https://en.wikipedia.org/wiki/Uniform_distribution_(continuous)

Implementations

impl<T> Uniform<T> where
    T: Real, 

pub fn new(a: T, b: T) -> Uniform<T>

Uniform distribution

Arguments

-\inf < a < b < \inf

a: lower bound b: upper bound

a < b

Panic

a >= b

Trait Implementations

impl<T> Continuous<T> for Uniform<T> where
    T: Real, 

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

Probability density function

Arguments

x:

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let distrib: Uniform<f64> = Uniform::new(-0.1, 0.3);
let x: f64 = 5.0;
let p: f64 = distrib.pdf(x);

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

Cumulative distribution function

Arguments

• x

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let distrib: Uniform<f64> = Uniform::new(0.0, 0.5);
let x: f64 = 0.3;
let p: f64 = distrib.cdf(x);

fn quantile(&self, q: T) -> T

Quantile function or inverse cdf

Arguments

• q: quantile 0 <= q <= 1

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let distrib: Uniform<f64> = Uniform::new(0.0, 0.5);
let q: f64 = 0.3;
let x: f64 = distrib.quantile(q);

fn mean(&self) -> T

Mean

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let a: f64 = 0.2;
let b: f64 = 0.5;

let distrib: Uniform<f64> = Uniform::new(a, b);
let mean: f64 = distrib.mean();
assert_eq!((a + b) / 2.0, mean);

fn variance(&self) -> T

Variance

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let distrib: Uniform<f64> = Uniform::new(0.2, 0.5);
let var: f64 = distrib.variance();

fn skewness(&self) -> T

Skewness

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let distrib: Uniform<f64> = Uniform::new(0.2, 0.5);
let skewness: f64 = distrib.skewness();
assert_eq!(0.0, skewness);

fn median(&self) -> T

Median

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let a: f64 = 0.2;
let b: f64 = 0.5;

let distrib: Uniform<f64> = Uniform::new(a, b);
let median: f64 = distrib.median();
assert_eq!((a + b) / 2.0, median);

fn entropy(&self) -> T

Entropy

Example

use mathru::statistics::distrib::{Continuous, Uniform};

let a: f64 = 0.2;
let b: f64 = 0.5;

let distrib: Uniform<f64> = Uniform::new(a, b);
let entropy: f64 = distrib.entropy();
assert_eq!((b - a).ln(), entropy);

impl<T> Distribution<T> for Uniform<T> where
    T: Real, 

fn random(&self) -> T

fn random_sequence(&self, size: u32) -> Vec<T>