https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor
Discrete uniform distribution constructor.
https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor
cdf class constructor ctor dist distribution javascript node node-js nodejs object pdf prob probability properties props quantile statistics stats stdlib
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Discrete uniform distribution constructor.
- Host: GitHub
- URL: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor
- Owner: stdlib-js
- License: apache-2.0
- Created: 2021-06-15T17:26:25.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-03-17T00:37:31.000Z (8 months ago)
- Last Synced: 2025-05-19T08:13:25.244Z (6 months ago)
- Topics: cdf, class, constructor, ctor, dist, distribution, javascript, node, node-js, nodejs, object, pdf, prob, probability, properties, props, quantile, statistics, stats, stdlib
- Language: JavaScript
- Homepage: https://github.com/stdlib-js/stdlib
- Size: 1.53 MB
- Stars: 3
- Watchers: 3
- 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
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README
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# Discrete Uniform
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> Discrete uniform distribution constructor.
## Installation
```bash
npm install @stdlib/stats-base-dists-discrete-uniform-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 DiscreteUniform = require( '@stdlib/stats-base-dists-discrete-uniform-ctor' );
```
#### DiscreteUniform( \[a, b] )
Returns a [discrete uniform][discrete-uniform-distribution] distribution object.
```javascript
var discreteUniform = new DiscreteUniform();
var mu = discreteUniform.mean;
// returns 0.5
```
By default, `a = 0` and `b = 1`. To create a distribution having a different `a` (minimum support) and `b` (maximum support), provide the corresponding arguments.
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var mu = discreteUniform.mean;
// returns 3.0
```
* * *
## discreteUniform
A [discrete uniform][discrete-uniform-distribution] distribution object has the following properties and methods...
### Writable Properties
#### discreteUniform.a
Minimum support of the distribution. `a` **must** be an integer smaller than or equal to `b`.
```javascript
var discreteUniform = new DiscreteUniform( -2, 2 );
var a = discreteUniform.a;
// returns -2
discreteUniform.a = 0;
a = discreteUniform.a;
// returns 0
```
#### discreteUniform.b
Maximum support of the distribution. `b` **must** be an integer larger than or equal to `a`.
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var b = discreteUniform.b;
// returns 4
discreteUniform.b = 3;
b = discreteUniform.b;
// returns 3
```
* * *
### Computed Properties
#### DiscreteUniform.prototype.entropy
Returns the [differential entropy][entropy].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var entropy = discreteUniform.entropy;
// returns ~2.197
```
#### DiscreteUniform.prototype.kurtosis
Returns the [excess kurtosis][kurtosis].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var kurtosis = discreteUniform.kurtosis;
// returns -1.23
```
#### DiscreteUniform.prototype.mean
Returns the [expected value][expected-value].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var mu = discreteUniform.mean;
// returns 8.0
```
#### DiscreteUniform.prototype.median
Returns the [median][median].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var median = discreteUniform.median;
// returns 8.0
```
#### DiscreteUniform.prototype.skewness
Returns the [skewness][skewness].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var skewness = discreteUniform.skewness;
// returns 0.0
```
#### DiscreteUniform.prototype.stdev
Returns the [standard deviation][standard-deviation].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var s = discreteUniform.stdev;
// returns ~2.582
```
#### DiscreteUniform.prototype.variance
Returns the [variance][variance].
```javascript
var discreteUniform = new DiscreteUniform( 4, 12 );
var s2 = discreteUniform.variance;
// returns ~6.667
```
* * *
### Methods
#### DiscreteUniform.prototype.cdf( x )
Evaluates the [cumulative distribution function][cdf] (CDF).
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var y = discreteUniform.cdf( 2.5 );
// returns ~0.333
```
#### DiscreteUniform.prototype.logcdf( x )
Evaluates the natural logarithm of the [cumulative distribution function][cdf] (CDF).
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var y = discreteUniform.logcdf( 2.5 );
// returns ~-1.099
```
#### DiscreteUniform.prototype.logpmf( x )
Evaluates the natural logarithm of the [probability mass function][pmf] (PMF).
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var y = discreteUniform.logpmf( 4.0 );
// returns ~-1.099
```
#### DiscreteUniform.prototype.pmf( x )
Evaluates the [probability mass function][pmf] (PMF).
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var y = discreteUniform.pmf( 3, 0 );
// returns ~0.333
```
#### DiscreteUniform.prototype.quantile( p )
Evaluates the [quantile function][quantile-function] at probability `p`.
```javascript
var discreteUniform = new DiscreteUniform( 2, 4 );
var y = discreteUniform.quantile( 0.5 );
// returns 3.0
y = discreteUniform.quantile( 1.9 );
// returns NaN
```
* * *
## Examples
```javascript
var DiscreteUniform = require( '@stdlib/stats-base-dists-discrete-uniform-ctor' );
var discreteUniform = new DiscreteUniform( -2, 2 );
var mu = discreteUniform.mean;
// returns 0.0
var median = discreteUniform.median;
// returns 0.0
var s2 = discreteUniform.variance;
// returns 2.0
var y = discreteUniform.cdf( 2.5 );
// returns 1.0
```
* * *
## 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 © 2016-2025. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-dists-discrete-uniform-ctor.svg
[npm-url]: https://npmjs.org/package/@stdlib/stats-base-dists-discrete-uniform-ctor
[test-image]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/actions/workflows/test.yml?query=branch:main
[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-dists-discrete-uniform-ctor/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/stats-base-dists-discrete-uniform-ctor?branch=main
[chat-image]: https://img.shields.io/gitter/room/stdlib-js/stdlib.svg
[chat-url]: https://app.gitter.im/#/room/#stdlib-js_stdlib:gitter.im
[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-discrete-uniform-ctor/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-discrete-uniform-ctor/main/LICENSE
[discrete-uniform-distribution]: https://en.wikipedia.org/wiki/Discrete_uniform_distribution
[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function
[pmf]: https://en.wikipedia.org/wiki/Probability_mass_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
[skewness]: https://en.wikipedia.org/wiki/Skewness
[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation
[variance]: https://en.wikipedia.org/wiki/Variance