Struct rv::dist::Laplace

pub struct Laplace { /* fields omitted */ }

Laplace, or double exponential, distribution

Example

extern crate rand;

use rv::prelude::*;

let laplace = Laplace::new(0.0, 1.0).expect("Invalid params");

// 100 draws from Laplace
let mut rng = rand::thread_rng();
let xs: Vec<f64> = laplace.sample(100, &mut rng);
assert_eq!(xs.len(), 100);

Methods

impl Laplace

pub fn new(mu: f64, b: f64) -> Result<Self>

Trait Implementations

impl Clone for Laplace

fn clone(&self) -> Laplace

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Laplace

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

Formats the value using the given formatter.

impl Default for Laplace

Laplace with mean 0 and variance 1

fn default() -> Self

Returns the "default value" for a type.

impl Skewness for Laplace

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

impl Kurtosis for Laplace

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

impl Entropy for Laplace

fn entropy(&self) -> f64

The entropy, H(X)

impl Rv<f64> for Laplace

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 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.

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

Multiple draws of the Rv

impl Support<f64> for Laplace

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

Returns true if x is in the support of the Rv

impl ContinuousDistr<f64> for Laplace

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 Laplace

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 Mean<f64> for Laplace

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

Returns None if the mean is undefined

impl Median<f64> for Laplace

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

Returns None if the median is undefined

impl Mode<f64> for Laplace

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

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

impl Variance<f64> for Laplace

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

Returns None if the variance is undefined

impl Rv<f32> for Laplace

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 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.

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

Multiple draws of the Rv

impl Support<f32> for Laplace

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

Returns true if x is in the support of the Rv

impl ContinuousDistr<f32> for Laplace

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 Laplace

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 Mean<f32> for Laplace

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

Returns None if the mean is undefined

impl Median<f32> for Laplace

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

Returns None if the median is undefined

impl Mode<f32> for Laplace

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

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

impl Variance<f32> for Laplace

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

Returns None if the variance is undefined