Struct rv::dist::Cauchy

pub struct Cauchy {
    pub loc: f64,
    pub scale: f64,
}

Cauchy distribution over x in (-∞, ∞)

Example

use rv::prelude::*;

let cauchy = Cauchy::new(1.2, 3.4).expect("Invalid params");
let ln_fx = cauchy.ln_pdf(&0.2_f64); // -2.4514716152673368

assert!((ln_fx + 2.4514716152673368).abs() < 1E-12);

Fields

loc: f64

location, x₀, in (-∞, ∞)

scale: f64

location, γ, in (0, ∞)

Methods

impl Cauchy

pub fn new(loc: f64, scale: f64) -> Result<Self>

Trait Implementations

impl Debug for Cauchy

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

Formats the value using the given formatter.

impl Clone for Cauchy

fn clone(&self) -> Cauchy

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Default for Cauchy

fn default() -> Self

Returns the "default value" for a type.

impl Entropy for Cauchy

fn entropy(&self) -> f64

The entropy, H(X)

impl Rv<f64> for Cauchy

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 Cauchy

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

Returns true if x is in the support of the Rv

impl ContinuousDistr<f64> for Cauchy

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 Cauchy

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 Cauchy

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 Median<f64> for Cauchy

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

Returns None if the median is undefined

impl Mode<f64> for Cauchy

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

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

impl Rv<f32> for Cauchy

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 Cauchy

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

Returns true if x is in the support of the Rv

impl ContinuousDistr<f32> for Cauchy

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 Cauchy

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 Cauchy

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 Median<f32> for Cauchy

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

Returns None if the median is undefined

impl Mode<f32> for Cauchy

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

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