# Struct rand_distr::LogNormal

``pub struct LogNormal<F>where    F: Float,    StandardNormal: Distribution<F>,{ /* private fields */ }``
Expand description

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)``````

## Implementations§

Construct, from (log-space) mean and standard deviation

Parameters are the “standard” log-space measures (these are the mean and standard deviation of the logarithm of samples):

• `mu` (`μ`, unrestricted) is the mean of the underlying distribution
• `sigma` (`σ`, must be finite) is the standard deviation of the underlying Normal distribution

Construct, from (linear-space) mean and coefficient of variation

Parameters are linear-space measures:

• mean (`μ > 0`) is the (real) mean of the distribution
• coefficient of variation (`cv = σ / μ`, requiring `cv ≥ 0`) is a standardized measure of dispersion

As a special exception, `μ = 0, cv = 0` is allowed (samples are `-inf`).

Sample from a z-score

This may be useful for generating correlated samples `x1` and `x2` from two different distributions, as follows.

``````let mut rng = thread_rng();
let z = StandardNormal.sample(&mut rng);
let x1 = LogNormal::from_mean_cv(3.0, 1.0).unwrap().from_zscore(z);
let x2 = LogNormal::from_mean_cv(2.0, 4.0).unwrap().from_zscore(z);``````

## Trait Implementations§

Returns a copy of the value. Read more
Performs copy-assignment from `source`. Read more
Formats the value using the given formatter. Read more
Deserialize this value from the given Serde deserializer. Read more
Generate a random value of `T`, using `rng` as the source of randomness.
Create an iterator that generates random values of `T`, using `rng` as the source of randomness. Read more
Create a distribution of values of ‘S’ by mapping the output of `Self` through the closure `F` Read more
This method tests for `self` and `other` values to be equal, and is used by `==`. Read more
This method tests for `!=`. The default implementation is almost always sufficient, and should not be overridden without very good reason. Read more
Serialize this value into the given Serde serializer. Read more

## Blanket Implementations§

Gets the `TypeId` of `self`. Read more
Immutably borrows from an owned value. Read more
Mutably borrows from an owned value. Read more

Returns the argument unchanged.

Calls `U::from(self)`.

That is, this conversion is whatever the implementation of `From<T> for U` chooses to do.

The resulting type after obtaining ownership.
Creates owned data from borrowed data, usually by cloning. Read more
Uses borrowed data to replace owned data, usually by cloning. Read more
The type returned in the event of a conversion error.
Performs the conversion.
The type returned in the event of a conversion error.
Performs the conversion.