Struct probability::distribution::Gaussian

pub struct Gaussian { /* fields omitted */ }

A Gaussian distribution.

Implementations

impl Gaussian

pub fn new(mu: f64, sigma: f64) -> Self

Create a Gaussian distribution with mean mu and standard deviation sigma.

It should hold that sigma > 0.

pub fn mu(&self) -> f64

Return the mean.

pub fn sigma(&self) -> f64

Return the standard deviation.

Trait Implementations

impl Clone for Gaussian

fn clone(&self) -> Gaussian

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Continuous for Gaussian

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

Compute the probability density function.

impl Copy for Gaussian

impl Debug for Gaussian

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

Formats the value using the given formatter.

impl Default for Gaussian

fn default() -> Self

Returns the “default value” for a type.

impl Distribution for Gaussian

type Value = f64

The type of outcomes.

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

Compute the cumulative distribution function.

impl Entropy for Gaussian

fn entropy(&self) -> f64

Compute the differential entropy.

impl Inverse for Gaussian

fn inverse(&self, p: f64) -> f64

Compute the inverse of the cumulative distribution function.

References

1. M. J. Wichura, “Algorithm as 241: The percentage points of the normal distribution,” Journal of the Royal Statistical Society. Series C (Applied Statistics), vol. 37, no. 3, pp. pp. 477–484, 1988.

2. http://people.sc.fsu.edu/~jburkardt/c_src/asa241/asa241.html

impl Kurtosis for Gaussian

fn kurtosis(&self) -> f64

Compute the excess kurtosis.

impl Mean for Gaussian

fn mean(&self) -> f64

Compute the expected value.

impl Median for Gaussian

fn median(&self) -> f64

Compute the median.

impl Modes for Gaussian

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

Compute the modes.

impl Sample for Gaussian

fn sample<S>(&self, source: &mut S) -> f64 where
    S: Source, 

Draw a sample.

References

1. G. Marsaglia and W. W. Tsang, “The ziggurat method for generating random variables,” Journal of Statistical Software, vol. 5, no. 8, pp. 1–7, 10 2000.

2. D. Eddelbuettel, “Ziggurat Revisited,” 2014.

impl Skewness for Gaussian

fn skewness(&self) -> f64

Compute the skewness.

impl Variance for Gaussian

fn variance(&self) -> f64

Compute the variance.

fn deviation(&self) -> f64

Compute the standard deviation.