Struct rstat::univariate::cauchy::Cauchy

pub struct Cauchy(_);

Methods

impl Cauchy

pub fn new(x0: f64, gamma: f64) -> Result<Cauchy, Error>

pub fn new_unchecked(x0: f64, gamma: f64) -> Cauchy

pub fn fwhm(&self) -> f64

Trait Implementations

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 ContinuousDistribution for Cauchy

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

Evaluates the probability density function (PDF) at (x).

fn log_pdf(&self, x: &Sample<Self>) -> f64

Evaluates the log PDF at (x).

impl Convolution<Cauchy> for Cauchy

type Output = Cauchy

The resulting Distribution type.

fn convolve(self, rv: Cauchy) -> Result<Cauchy, Error>

Return the unweighted linear sum of self with another Distribution of type T.

fn convolve_many(self, rvs: Vec<T>) -> Result<Self::Output, Error> where
    Self::Output: Convolution<T, Output = Self::Output>,
    Self: Sized, 

Return the unweighted linear sum of self with a set of Distributions of type T.

impl Copy for Cauchy

impl Debug for Cauchy

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

Formats the value using the given formatter.

impl Default for Cauchy

fn default() -> Cauchy

Returns the "default value" for a type.

impl Display for Cauchy

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

Formats the value using the given formatter.

impl Distribution for Cauchy

type Support = Reals

Support of sample elements.

type Params = Params

Parameter set uniquely defining the instance.

fn support(&self) -> Reals

Returns an instance of the support Space, Self::Support.

fn params(&self) -> Params

Returns an instance of Self::Params matching the parameters of self.

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

Evaluates the cumulative distribution function (CDF) at (x).

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

Draw a random value from the distribution support.

fn into_support(self) -> Self::Support

fn into_params(self) -> Self::Params

fn ccdf(&self, x: &Sample<Self>) -> Probability

Evaluates the complementary CDF at (x).

fn log_cdf(&self, x: &Sample<Self>) -> f64

Evaluates the log CDF at (x), i.e. (\ln{F(x)}).

fn log_ccdf(&self, x: &Sample<Self>) -> f64

Evaluates the log complementary CDF at (x), i.e. (\ln{(1 - F(x))}).

fn sample_n<R: Rng + ?Sized>(&self, rng: &mut R, n: usize) -> Vec<Sample<Self>>

Draw n random value from the distribution support.

fn sample_iter<'a, R: Rng + ?Sized>(
    &'a self,
    rng: &'a mut R
) -> Sampler<'a, Self, R>

Draw an indefinite number of random values from the distribution support.

impl Entropy for Cauchy

fn entropy(&self) -> f64

Computes the entropy value of the distribution, H(X).

impl From<Params> for Cauchy

fn from(from: Params) -> Cauchy

Performs the conversion.

impl Modes for Cauchy

fn modes(&self) -> Vec<f64>

Computes the mode(s) of the distribution.

impl Quantiles for Cauchy

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

Evaluates the inverse cumulative distribution function (CDF) at p.

fn median(&self) -> f64

Computes the median value of the distribution, Q(0.5).

fn cquantile(&self, p: Probability) -> f64

Evaluates the complementary quantile function at x: Q(1 - p).

fn lower_quartile(&self) -> f64

Computes the lower quartile of the distribution, Q(0.25).

fn upper_quartile(&self) -> f64

Computes the upper quartile of the distribution, Q(0.75).

fn iqr(&self) -> f64

Computes the interquartile range (IQR) of the distribution, Q(0.75) - Q(0.25).

fn lower_fence(&self) -> f64

Computes the lower fence of the distribution, Q(0.25) - 1.5 · IQR.

fn upper_fence(&self) -> f64

Computes the lower fence of the distribution, Q(0.75) + 1.5 · IQR.