Struct statrs::distribution::Exponential

pub struct Exponential { /* fields omitted */ }

Implements the Exponential distribution and is a special case of the Gamma distribution (referenced here)

Examples

use statrs::distribution::{Exponential, Continuous};
use statrs::statistics::Mean;

let n = Exponential::new(1.0).unwrap();
assert_eq!(n.mean(), 1.0);
assert_eq!(n.pdf(1.0), 0.3678794411714423215955);

Methods

impl Exponential

pub fn new(rate: f64) -> Result<Exponential>

Constructs a new exponential distribution with a rate (λ) of rate.

Errors

Returns an error if rate is NaN or rate <= 0.0

Examples

use statrs::distribution::Exponential;

let mut result = Exponential::new(1.0);
assert!(result.is_ok());

result = Exponential::new(-1.0);
assert!(result.is_err());

pub fn rate(&self) -> f64

Returns the rate of the exponential distribution

Examples

use statrs::distribution::Exponential;

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

Trait Implementations

impl Univariate<f64, f64> for Exponential

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

Calculates the cumulative distribution function for the exponential distribution at x

Formula

1 - e^(-λ * x)

where λ is the rate

impl Continuous<f64, f64> for Exponential

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

Calculates the probability density function for the exponential distribution at x

Formula

λ * e^(-λ * x)

where λ is the rate

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

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

Formula

ln(λ * e^(-λ * x))

where λ is the rate

impl Min<f64> for Exponential

fn min(&self) -> f64

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

Formula

0

impl Max<f64> for Exponential

fn max(&self) -> f64

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

Formula

INF

impl Mean<f64> for Exponential

fn mean(&self) -> f64

Returns the mean of the exponential distribution

Formula

1 / λ

where λ is the rate

impl Variance<f64> for Exponential

fn variance(&self) -> f64

Returns the variance of the exponential distribution

Formula

1 / λ^2

where λ is the rate

fn std_dev(&self) -> f64

Returns the standard deviation of the exponential distribution

Formula

sqrt(1 / λ^2)

where λ is the rate

impl Entropy<f64> for Exponential

fn entropy(&self) -> f64

Returns the entropy of the exponential distribution

Formula

1 - ln(λ)

where λ is the rate

impl Skewness<f64> for Exponential

fn skewness(&self) -> f64

Returns the skewness of the exponential distribution

Formula

2

impl Median<f64> for Exponential

fn median(&self) -> f64

Returns the median of the exponential distribution

Formula

(1 / λ) * ln2

where λ is the rate

impl Mode<f64> for Exponential

fn mode(&self) -> f64

Returns the mode of the exponential distribution

Formula

0

impl Copy for Exponential

impl Clone for Exponential

fn clone(&self) -> Exponential

Returns a copy of the value.

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

Performs copy-assignment from source.

impl PartialEq<Exponential> for Exponential

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

This method tests for self and other values to be equal, and is used by ==.

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

This method tests for !=.

impl Debug for Exponential

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

Formats the value using the given formatter.

impl Distribution<f64> for Exponential

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

Generate a random value of T, using rng as the source of randomness.

fn sample_iter<R>(&'a self, rng: &'a mut R) -> DistIter<'a, Self, R, T> where
    R: Rng, 

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