Struct rv::dist::ChiSquared

pub struct ChiSquared {
    pub k: f64,
}

Χ² distribution G(α, β)

Example

use rv::prelude::*;

let x2 = ChiSquared::new(2.0).unwrap();

Fields

k: f64

Degrees of freedom in (0, ∞)

Methods

impl ChiSquared

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

Trait Implementations

impl Debug for ChiSquared

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

Formats the value using the given formatter.

impl Clone for ChiSquared

fn clone(&self) -> ChiSquared

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Skewness for ChiSquared

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

impl Kurtosis for ChiSquared

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

impl Rv<f64> for ChiSquared

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 ChiSquared

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

Returns true if x is in the support of the Rv

impl ContinuousDistr<f64> for ChiSquared

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 Mean<f64> for ChiSquared

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

Returns None if the mean is undefined

impl Mode<f64> for ChiSquared

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

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

impl Variance<f64> for ChiSquared

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

Returns None if the variance is undefined

impl Cdf<f64> for ChiSquared

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 Rv<f32> for ChiSquared

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 ChiSquared

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

Returns true if x is in the support of the Rv

impl ContinuousDistr<f32> for ChiSquared

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 Mean<f32> for ChiSquared

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

Returns None if the mean is undefined

impl Mode<f32> for ChiSquared

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

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

impl Variance<f32> for ChiSquared

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

Returns None if the variance is undefined

impl Cdf<f32> for ChiSquared

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)