npm package: @stdlib/stats-base-dists-lognormal-ctor
Description: Lognormal distribution constructor.
Author: The Stdlib Authors
Latest version: 0.2.3

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# Lognormal

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> Lognormal distribution constructor.

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dists-lognormal-ctor
```

</section>

<section class="usage">

## Usage

```javascript
var LogNormal = require( '@stdlib/stats-base-dists-lognormal-ctor' );
```

#### LogNormal( \[mu, sigma] )

Returns a [lognormal][lognormal-distribution] distribution object.

```javascript
var lognormal = new LogNormal();

var mean = lognormal.mean;
// returns ~1.649
```

By default, `mu = 0.0` and `sigma = 1.0`. To create a distribution having a different `mu` (location parameter) and `sigma` (scale parameter), provide the corresponding arguments.

```javascript
var lognormal = new LogNormal( 2.0, 4.0 );

var mu = lognormal.mean;
// returns ~22026.466
```

* * *

## lognormal

A [lognormal][lognormal-distribution] distribution object has the following properties and methods...

### Writable Properties

#### lognormal.mu

Location parameter of the distribution.

```javascript
var lognormal = new LogNormal();

var mu = lognormal.mu;
// returns 0.0

lognormal.mu = 3.0;

mu = lognormal.mu;
// returns 3.0
```

#### lognormal.sigma

Scale parameter of the distribution. `sigma` **must** be a positive number.

```javascript
var lognormal = new LogNormal( 2.0, 4.0 );

var sigma = lognormal.sigma;
// returns 4.0

lognormal.sigma = 3.0;

sigma = lognormal.sigma;
// returns 3.0
```

* * *

### Computed Properties

#### LogNormal.prototype.entropy

Returns the [differential entropy][entropy].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var entropy = lognormal.entropy;
// returns ~7.904
```

#### LogNormal.prototype.kurtosis

Returns the [excess kurtosis][kurtosis].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var kurtosis = lognormal.kurtosis;
// returns 1.4243659274306933e+250
```

#### LogNormal.prototype.mean

Returns the [expected value][expected-value].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var mu = lognormal.mean;
// returns 1.0148003881138887e+33
```

#### LogNormal.prototype.median

Returns the [median][median].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var median = lognormal.median;
// returns ~54.598
```

#### LogNormal.prototype.mode

Returns the [mode][mode].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var mode = lognormal.mode;
// returns 1.580420060273613e-61
```

#### LogNormal.prototype.skewness

Returns the [skewness][skewness].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var skewness = lognormal.skewness;
// returns 6.421080152185613e+93
```

#### LogNormal.prototype.stdev

Returns the [standard deviation][standard-deviation].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var s = lognormal.stdev;
// returns 1.886180808490652e+64
```

#### LogNormal.prototype.variance

Returns the [variance][variance].

```javascript
var lognormal = new LogNormal( 4.0, 12.0 );

var s2 = lognormal.variance;
// returns 3.55767804231845e+128
```

* * *

### Methods

#### LogNormal.prototype.cdf( x )

Evaluates the [cumulative distribution function][cdf] (CDF).

```javascript
var lognormal = new LogNormal( 2.0, 4.0 );

var y = lognormal.cdf( 0.5 );
// returns ~0.25
```

#### LogNormal.prototype.logcdf( x )

Evaluates the natural logarithm of the [cumulative distribution function][cdf] (CDF).

```javascript
var lognormal = new LogNormal( 0.0, 1.0 );

var y = lognormal.logcdf( 2.0 );
// returns ~-0.2799
```

#### LogNormal.prototype.logpdf( x )

Evaluates the natural logarithm of the [probability density function][pdf] (PDF).

```javascript
var lognormal = new LogNormal( 2.0, 4.0 );

var y = lognormal.logpdf( 2.0 );
// returns ~-3.052
```

#### LogNormal.prototype.pdf( x )

Evaluates the [probability density function][pdf] (PDF).

```javascript
var lognormal = new LogNormal( 2.0, 4.0 );

var y = lognormal.pdf( 2.0 );
// returns ~0.047
```

#### LogNormal.prototype.quantile( p )

Evaluates the [quantile function][quantile-function] at probability `p`.

```javascript
var lognormal = new LogNormal( 2.0, 4.0 );

var y = lognormal.quantile( 0.5 );
// returns ~7.389

y = lognormal.quantile( 1.9 );
// returns NaN
```

</section>

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<section class="notes">

</section>

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<!-- Package usage examples. -->

* * *

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var LogNormal = require( '@stdlib/stats-base-dists-lognormal-ctor' );

var lognormal = new LogNormal( 2.0, 1.0 );

var mean = lognormal.mean;
// returns ~12.182

var median = lognormal.median;
// returns ~7.389

var s2 = lognormal.variance;
// returns ~255.016

var y = lognormal.cdf( 0.8 );
// returns ~0.013
```

</section>

<!-- /.examples -->

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* * *

## Notice

This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].

#### Community

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-lognormal-ctor/main/LICENSE

[lognormal-distribution]: https://en.wikipedia.org/wiki/Log-normal_distribution

[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function

[pdf]: https://en.wikipedia.org/wiki/Probability_density_function

[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function

[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29

[expected-value]: https://en.wikipedia.org/wiki/Expected_value

[kurtosis]: https://en.wikipedia.org/wiki/Kurtosis

[median]: https://en.wikipedia.org/wiki/Median

[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29

[skewness]: https://en.wikipedia.org/wiki/Skewness

[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation

[variance]: https://en.wikipedia.org/wiki/Variance

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