https://github.com/stdlib-js/stats-base-dists-exponential-ctor
Exponential distribution constructor.
https://github.com/stdlib-js/stats-base-dists-exponential-ctor
cdf class constructor ctor dist distribution exponential javascript node node-js nodejs object pdf prob probability properties quantile statistics stats stdlib
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Exponential distribution constructor.
- Host: GitHub
- URL: https://github.com/stdlib-js/stats-base-dists-exponential-ctor
- Owner: stdlib-js
- License: apache-2.0
- Created: 2021-06-15T17:26:10.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2026-03-25T03:54:31.000Z (2 months ago)
- Last Synced: 2026-03-26T09:20:49.339Z (2 months ago)
- Topics: cdf, class, constructor, ctor, dist, distribution, exponential, javascript, node, node-js, nodejs, object, pdf, prob, probability, properties, quantile, statistics, stats, stdlib
- Language: JavaScript
- Homepage: https://github.com/stdlib-js/stdlib
- Size: 1.83 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Security: SECURITY.md
- Notice: NOTICE
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README
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# Exponential
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> Exponential distribution constructor.
## Installation
```bash
npm install @stdlib/stats-base-dists-exponential-ctor
```
Alternatively,
- To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]).
- If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).
- For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]).
The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
## Usage
```javascript
var Exponential = require( '@stdlib/stats-base-dists-exponential-ctor' );
```
#### Exponential( \[lambda] )
Returns an [exponential][exponential-distribution] distribution object.
```javascript
var exponential = new Exponential();
var mu = exponential.mean;
// returns 1.0
```
By default, `lambda = 1.0`. To create a distribution having a different rate parameter `lambda`, provide a parameter value.
```javascript
var exponential = new Exponential( 4.0 );
var mu = exponential.mean;
// returns 0.25
```
* * *
## exponential
An [exponential][exponential-distribution] distribution object has the following properties and methods...
### Writable Properties
#### exponential.lambda
Rate parameter of the distribution. `lambda` **must** be a positive number.
```javascript
var exponential = new Exponential( 2.0 );
var lambda = exponential.lambda;
// returns 2.0
exponential.lambda = 3.0;
lambda = exponential.lambda;
// returns 3.0
```
* * *
### Computed Properties
#### Exponential.prototype.entropy
Returns the [differential entropy][entropy].
```javascript
var exponential = new Exponential( 4.0 );
var entropy = exponential.entropy;
// returns ~-0.386
```
#### Exponential.prototype.kurtosis
Returns the [excess kurtosis][kurtosis].
```javascript
var exponential = new Exponential( 4.0 );
var kurtosis = exponential.kurtosis;
// returns 6.0
```
#### Exponential.prototype.mean
Returns the [expected value][expected-value].
```javascript
var exponential = new Exponential( 4.0 );
var mu = exponential.mean;
// returns 0.25
```
#### Exponential.prototype.median
Returns the [median][median].
```javascript
var exponential = new Exponential( 4.0 );
var median = exponential.median;
// returns ~0.173
```
#### Exponential.prototype.mode
Returns the [mode][mode].
```javascript
var exponential = new Exponential( 4.0 );
var mode = exponential.mode;
// returns 0.0
```
#### Exponential.prototype.skewness
Returns the [skewness][skewness].
```javascript
var exponential = new Exponential( 4.0 );
var skewness = exponential.skewness;
// returns 2.0
```
#### Exponential.prototype.stdev
Returns the [standard deviation][standard-deviation].
```javascript
var exponential = new Exponential( 4.0 );
var s = exponential.stdev;
// returns 0.25
```
#### Exponential.prototype.variance
Returns the [variance][variance].
```javascript
var exponential = new Exponential( 4.0 );
var s2 = exponential.variance;
// returns ~0.063
```
* * *
### Methods
#### Exponential.prototype.cdf( x )
Evaluates the [cumulative distribution function][cdf] (CDF).
```javascript
var exponential = new Exponential( 2.0 );
var y = exponential.cdf( 0.5 );
// returns ~0.632
```
#### Exponential.prototype.logcdf( x )
Evaluates the natural logarithm of the [cumulative distribution function][cdf] (CDF).
```javascript
var exponential = new Exponential( 2.0 );
var y = exponential.logcdf( 0.5 );
// returns ~-0.459
```
#### Exponential.prototype.logpdf( x )
Evaluates the natural logarithm of the [probability density function][pdf] (PDF).
```javascript
var exponential = new Exponential( 2.0 );
var y = exponential.logpdf( 0.8 );
// returns ~-0.907
```
#### Exponential.prototype.mgf( t )
Evaluates the [moment-generating function][mgf] (MGF).
```javascript
var exponential = new Exponential( 2.0 );
var y = exponential.mgf( 0.5 );
// returns ~1.333
```
#### Exponential.prototype.pdf( x )
Evaluates the [probability density function][pdf] (PDF).
```javascript
var exponential = new Exponential( 2.0 );
var y = exponential.pdf( 0.8 );
// returns ~0.404
```
#### Exponential.prototype.quantile( p )
Evaluates the [quantile function][quantile-function] at probability `p`.
```javascript
var exponential = new Exponential( 2.0 );
var y = exponential.quantile( 0.5 );
// returns ~0.347
y = exponential.quantile( 1.9 );
// returns NaN
```
* * *
## Examples
```javascript
var Exponential = require( '@stdlib/stats-base-dists-exponential-ctor' );
var exponential = new Exponential( 2.0 );
var mu = exponential.mean;
// returns 0.5
var mode = exponential.mode;
// returns 0.0
var s2 = exponential.variance;
// returns 0.25
var y = exponential.cdf( 0.8 );
// returns ~0.798
```
* * *
## 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
[![Chat][chat-image]][chat-url]
---
## License
See [LICENSE][stdlib-license].
## Copyright
Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-dists-exponential-ctor.svg
[npm-url]: https://npmjs.org/package/@stdlib/stats-base-dists-exponential-ctor
[test-image]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/actions/workflows/test.yml?query=branch:main
[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-dists-exponential-ctor/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/stats-base-dists-exponential-ctor?branch=main
[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg
[chat-url]: https://stdlib.zulipchat.com
[stdlib]: https://github.com/stdlib-js/stdlib
[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors
[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-exponential-ctor/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-exponential-ctor/main/LICENSE
[exponential-distribution]: https://en.wikipedia.org/wiki/Exponential_distribution
[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function
[mgf]: https://en.wikipedia.org/wiki/Moment-generating_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