Struct rv::dist::Exponential

pub struct Exponential {
    pub rate: f64,
}

Exponential distribution, Exp(λ) over x in [0, ∞)

Examples

Compute 50% confidence interval

use rv::prelude::*;

let expon = Exponential::new(1.5).unwrap();
let interval: (f64, f64) = expon.interval(0.5);  // (0.19, 0.92)

Fields

rate: f64

λ > 0, rate or inverse scale

Methods

impl Exponential

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

Trait Implementations

impl Debug for Exponential

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

Formats the value using the given formatter.

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 Skewness for Exponential

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

impl Kurtosis for Exponential

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

impl Entropy for Exponential

fn entropy(&self) -> f64

The entropy, H(X)

impl KlDivergence for Exponential

fn kl(&self, other: &Self) -> f64

The KL divergence, KL(P|Q) between this distribution, P, and another, Q

fn kl_sym(&self, other: &Self) -> f64

Symmetrised divergence, KL(P|Q) + KL(Q|P)

impl Rv<f64> for Exponential

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

Un-normalized probability function

fn ln_normalizer(&self) -> f64

The log of the constant term in the PDF/PMF. Should not be a function of any of the parameters.

fn draw<R: Rng>(&self, rng: &mut R) -> f64

Single draw from the Rv

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<f64>

Multiple draws of the Rv

fn f(&self, x: &X) -> f64

Un-normalized probability function

fn normalizer(&self) -> f64

The constant term in the PDF/PMF. Should not be a function of any of the parameters.

impl Support<f64> for Exponential

fn contains(&self, x: &f64) -> bool

Returns true if x is in the support of the Rv

impl ContinuousDistr<f64> for Exponential

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

The value of the Probability Density Function (PDF) at x

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

The value of the log Probability Density Function (PDF) at x

impl Cdf<f64> for Exponential

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

The value of the Cumulative Density Function at x

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

Survival function, 1 - CDF(x)

impl InverseCdf<f64> for Exponential

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

The value of the x at the given probability in the CDF

fn quantile(&self, p: f64) -> X

Alias for invcdf

fn interval(&self, p: f64) -> (X, X)

Interval containing p proportion for the probability

impl Mean<f64> for Exponential

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

Returns None if the mean is undefined

impl Median<f64> for Exponential

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

Returns None if the median is undefined

impl Mode<f64> for Exponential

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

Returns None if the mode is undefined or is not a single value

impl Variance<f64> for Exponential

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

Returns None if the variance is undefined

impl Rv<f32> for Exponential

fn ln_f(&self, x: &f32) -> f64

Un-normalized probability function

fn ln_normalizer(&self) -> f64

The log of the constant term in the PDF/PMF. Should not be a function of any of the parameters.

fn draw<R: Rng>(&self, rng: &mut R) -> f32

Single draw from the Rv

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<f32>

Multiple draws of the Rv

fn f(&self, x: &X) -> f64

Un-normalized probability function

fn normalizer(&self) -> f64

The constant term in the PDF/PMF. Should not be a function of any of the parameters.

impl Support<f32> for Exponential

fn contains(&self, x: &f32) -> bool

Returns true if x is in the support of the Rv

impl ContinuousDistr<f32> for Exponential

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

The value of the Probability Density Function (PDF) at x

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

The value of the log Probability Density Function (PDF) at x

impl Cdf<f32> for Exponential

fn cdf(&self, x: &f32) -> f64

The value of the Cumulative Density Function at x

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

Survival function, 1 - CDF(x)

impl InverseCdf<f32> for Exponential

fn invcdf(&self, p: f64) -> f32

The value of the x at the given probability in the CDF

fn quantile(&self, p: f64) -> X

Alias for invcdf

fn interval(&self, p: f64) -> (X, X)

Interval containing p proportion for the probability

impl Mean<f32> for Exponential

fn mean(&self) -> Option<f32>

Returns None if the mean is undefined

impl Median<f32> for Exponential

fn median(&self) -> Option<f32>

Returns None if the median is undefined

impl Mode<f32> for Exponential

fn mode(&self) -> Option<f32>

Returns None if the mode is undefined or is not a single value

impl Variance<f32> for Exponential

fn variance(&self) -> Option<f32>

Returns None if the variance is undefined