Struct rand_distr::LogNormal

pub struct LogNormal<N> { /* 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_distr::{LogNormal, Distribution};

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

Methods

impl<N: Float> LogNormal<N> where
    StandardNormal: Distribution<N>, 

pub fn new(mean: N, std_dev: N) -> Result<LogNormal<N>, Error>

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

Trait Implementations

impl<N: Copy> Copy for LogNormal<N>

impl<N: Clone> Clone for LogNormal<N>

fn clone(&self) -> LogNormal<N>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N: Debug> Debug for LogNormal<N>

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

Formats the value using the given formatter.

impl<N: Float> Distribution<N> for LogNormal<N> where
    StandardNormal: Distribution<N>, 

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

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

Important traits for DistIter<D, R, T>

impl<D, R, T> Iterator for DistIter<D, R, T> where
    D: Distribution<T>,
    R: Rng,  type Item = T;

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.