npm package: @stdlib/stats-base-dists-laplace-skewness
Description: Laplace distribution skewness.
Author: The Stdlib Authors
Latest version: 0.3.1

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# Skewness

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> [Laplace][laplace-distribution] distribution [skewness][skewness].

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<section class="intro">

The [skewness][skewness] for a [Laplace][laplace-distribution] random variable with location parameter `mu` and scale parameter `b > 0` is

<!-- <equation class="equation" label="eq:laplace_skewness" align="center" raw="\operatorname{skew}\left( X \right) = 0" alt="Skewness for a Laplace distribution."> -->

<div class="equation" align="center" data-raw-text="\operatorname{skew}\left( X \right) = 0" data-equation="eq:laplace_skewness">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@51534079fef45e990850102147e8945fb023d1d0/lib/node_modules/@stdlib/stats/base/dists/laplace/skewness/docs/img/equation_laplace_skewness.svg" alt="Skewness for a Laplace distribution.">
    <br>
</div>

<!-- </equation> -->

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dists-laplace-skewness
```

</section>

<section class="usage">

## Usage

```javascript
var skewness = require( '@stdlib/stats-base-dists-laplace-skewness' );
```

#### skewness( mu, b )

Returns the [skewness][skewness] for a [Laplace][laplace-distribution] distribution with location parameter `mu` and scale parameter `b`.

```javascript
var y = skewness( 2.0, 1.0 );
// returns 0.0

y = skewness( 0.0, 1.0 );
// returns 0.0

y = skewness( -1.0, 4.0 );
// returns 0.0
```

If provided `NaN` as any argument, the function returns `NaN`.

```javascript
var y = skewness( NaN, 1.0 );
// returns NaN

y = skewness( 0.0, NaN );
// returns NaN
```

If provided `b <= 0`, the function returns `NaN`.

```javascript
var y = skewness( 0.0, 0.0 );
// returns NaN

y = skewness( 0.0, -1.0 );
// returns NaN
```

</section>

<!-- /.usage -->

<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- Package usage examples. -->

<section class="examples">

## Examples

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

```javascript
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var skewness = require( '@stdlib/stats-base-dists-laplace-skewness' );

var opts = {
    'dtype': 'float64'
};
var mu = uniform( 10, -5.0, 5.0, opts );
var b = uniform( 10, 0.0, 20.0, opts );

logEachMap( 'µ: %0.4f, b: %0.4f, skew(X;µ,b): %0.4f', mu, b, skewness );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

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<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/base/dists/laplace/skewness.h"
```

#### stdlib_base_dists_laplace_skewness( mu, b )

Evaluates the [skewness][skewness] for a [Laplace][laplace-distribution] distribution with location parameter `mu` and scale parameter `b`.

```c
double out = stdlib_base_dists_laplace_skewness( 0.0, 1.0 );
// returns 0.0
```

The function accepts the following arguments:

-   **mu**: `[in] double` location parameter.
-   **b**: `[in] double` scale parameter.

```c
double stdlib_base_dists_laplace_skewness( const double mu, const double b );
```

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/stats/base/dists/laplace/skewness.h"
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
    return min + ( v*(max-min) );
}

int main( void ) {
    double mu;
    double b;
    double y;
    int i;

    for ( i = 0; i < 25; i++ ) {
        mu = random_uniform( -5.0, 5.0 );
        b = random_uniform( 0.0, 20.0 );
        y = stdlib_base_dists_laplace_skewness( mu, b );
        printf( "µ: %lf, b: %lf, skew(X;µ,b): %lf\n", mu, b, y );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

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</section>

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<section class="main-repo" >

* * *

## 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].

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---

## License

See [LICENSE][stdlib-license].


## Copyright

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

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[laplace-distribution]: https://en.wikipedia.org/wiki/Laplace_distribution

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

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