Struct statrs::distribution::Dirac

pub struct Dirac(_);

Implements the Dirac Delta distribution

Examples

use statrs::distribution::{Dirac, Continuous};
use statrs::statistics::Distribution;

let n = Dirac::new(3.0).unwrap();
assert_eq!(n.mean().unwrap(), 3.0);

Implementations

impl Dirac

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

Constructs a new dirac distribution function at value v.

Errors

Returns an error if v is not-a-number.

Examples

use statrs::distribution::Dirac;

let mut result = Dirac::new(0.0);
assert!(result.is_ok());

result = Dirac::new(f64::NAN);
assert!(result.is_err());

Trait Implementations

impl Clone for Dirac

fn clone(&self) -> Dirac

Returns a copy of the value.

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

Performs copy-assignment from source.

impl ContinuousCDF<f64, f64> for Dirac

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

Calculates the cumulative distribution function for the dirac distribution at x

Where the value is 1 if x > v, 0 otherwise.

fn inverse_cdf(&self, p: T) -> K

Due to issues with rounding and floating-point accuracy the default implementation may be ill-behaved. Specialized inverse cdfs should be used whenever possible. Performs a binary search on the domain of cdf to obtain an approximation of F^-1(p) := inf { x | F(x) >= p }. Needless to say, performance may may be lacking.

impl Debug for Dirac

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

Formats the value using the given formatter.

impl Distribution<f64> for Dirac

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

Returns the mean of the dirac distribution

Remarks

Since the only value that can be produced by this distribution is v with probability 1, it is just v.

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

Returns the variance of the dirac distribution

Formula

0

Since only one value can be produced there is no variance.

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

Returns the entropy of the dirac distribution

Formula

0

Since this distribution has full certainty, it encodes no information

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

Returns the skewness of the dirac distribution

Formula

0

fn std_dev(&self) -> Option<T>

Returns the standard deviation, if it exists.

impl Distribution<f64> for Dirac

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

Generate a random value of T, using rng as the source of randomness.

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
    R: Rng, 

Create an iterator that generates random values of T, using rng as the source of randomness.

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S> where
    F: Fn(T) -> S, 

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

impl Max<f64> for Dirac

fn max(&self) -> f64

Returns the maximum value in the domain of the dirac distribution representable by a double precision float

Formula

v

impl Median<f64> for Dirac

fn median(&self) -> f64

Returns the median of the dirac distribution

Formula

v

where v is the point of the dirac distribution

impl Min<f64> for Dirac

fn min(&self) -> f64

Returns the minimum value in the domain of the dirac distribution representable by a double precision float

Formula

v

impl Mode<Option<f64>> for Dirac

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

Returns the mode of the dirac distribution

Formula

v

where v is the point of the dirac distribution

impl PartialEq<Dirac> for Dirac

fn eq(&self, other: &Dirac) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Dirac) -> bool

This method tests for !=.

impl Copy for Dirac

impl StructuralPartialEq for Dirac