Struct rand::distributions::LogNormal

pub struct LogNormal { /* fields omitted */ }

The log-normal distribution ln N(mean, std_dev**2).

If X is log-normal distributed, then ln(X) is N(mean, std_dev**2) distributed.

Example

use rand::distributions::{LogNormal, Distribution};

// mean 2, standard deviation 3
let log_normal = LogNormal::new(2.0, 3.0);
let v = log_normal.sample(&mut rand::thread_rng());
println!("{} is from an ln N(2, 9) distribution", v)

Methods

impl LogNormal

pub fn new(mean: f64, std_dev: f64) -> LogNormal

Construct a new LogNormal distribution with the given mean and standard deviation.

Panics

Panics if std_dev < 0.

Trait Implementations

impl Sample<f64> for LogNormal

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

Deprecated since 0.5.0

: use Distribution instead

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

impl IndependentSample<f64> for LogNormal

fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64

Deprecated since 0.5.0

: use Distribution instead

Generate a random value.

impl Distribution<f64> for LogNormal

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

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

Important traits for DistIter<'a, D, R, T>

impl<'a, D, R, T> Iterator for DistIter<'a, D, R, T> where
    D: Distribution<T>,
    R: Rng + 'a,  type Item = T;

fn sample_iter<'a, R>(&'a self, rng: &'a mut R) -> DistIter<'a, Self, R, T> where     Self: Sized,     R: Rng,

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

impl Clone for LogNormal

fn clone(&self) -> LogNormal

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Copy for LogNormal

impl Debug for LogNormal

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

Formats the value using the given formatter.