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

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</details>

# Uniform

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

> Uniform 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-uniform-ctor
```

</section>

<section class="usage">

## Usage

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

#### Uniform( \[a, b] )

Returns an [uniform][uniform-distribution] distribution object.

```javascript
var uniform = new Uniform();

var mu = uniform.mean;
// returns 0.5
```

By default, `a = 0.0` and `b = 1.0`. To create a distribution having a different `a` (minimum support) and `b` (maximum support), provide the corresponding arguments.

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var mu = uniform.mean;
// returns 3.0
```

* * *

## uniform

An [uniform][uniform-distribution] distribution object has the following properties and methods...

### Writable Properties

#### uniform.a

Minimum support of the distribution. `a` **must** be a number smaller than `b`.

```javascript
var uniform = new Uniform();

var a = uniform.a;
// returns 0.0

uniform.a = 0.5;

a = uniform.a;
// returns 0.5
```

#### uniform.b

Maximum support of the distribution. `b` **must** be a number larger than `a`.

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var b = uniform.b;
// returns 4.0

uniform.b = 3.0;

b = uniform.b;
// returns 3.0
```

* * *

### Computed Properties

#### Uniform.prototype.entropy

Returns the [differential entropy][entropy].

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var entropy = uniform.entropy;
// returns ~2.079
```

#### Uniform.prototype.kurtosis

Returns the [excess kurtosis][kurtosis].

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var kurtosis = uniform.kurtosis;
// returns -1.2
```

#### Uniform.prototype.mean

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

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var mu = uniform.mean;
// returns 8.0
```

#### Uniform.prototype.median

Returns the [median][median].

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var median = uniform.median;
// returns 8.0
```

#### Uniform.prototype.skewness

Returns the [skewness][skewness].

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var skewness = uniform.skewness;
// returns 0.0
```

#### Uniform.prototype.stdev

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

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var s = uniform.stdev;
// returns ~2.309
```

#### Uniform.prototype.variance

Returns the [variance][variance].

```javascript
var uniform = new Uniform( 4.0, 12.0 );

var s2 = uniform.variance;
// returns ~5.333
```

* * *

### Methods

#### Uniform.prototype.cdf( x )

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

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var y = uniform.cdf( 2.5 );
// returns 0.25
```

#### Uniform.prototype.logcdf( x )

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

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var y = uniform.logcdf( 2.5 );
// returns ~-1.386
```

#### Uniform.prototype.logpdf( x )

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

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var y = uniform.logpdf( 2.5 );
// returns ~-0.693
```

#### Uniform.prototype.pdf( x )

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

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var y = uniform.pdf( 2.5 );
// returns 0.5
```

#### Uniform.prototype.quantile( p )

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

```javascript
var uniform = new Uniform( 2.0, 4.0 );

var y = uniform.quantile( 0.5 );
// returns 3.0

y = uniform.quantile( 1.9 );
// 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>

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<!-- Package usage examples. -->

* * *

<section class="examples">

## Examples

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

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

var uniform = new Uniform( 2.0, 4.0 );

var mu = uniform.mean;
// returns 3.0

var median = uniform.median;
// returns 3.0

var s2 = uniform.variance;
// returns ~0.333

var y = uniform.cdf( 2.5 );
// returns 0.25
```

</section>

<!-- /.examples -->

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</section>

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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].

#### Community

[![Chat][chat-image]][chat-url]

---

## License

See [LICENSE][stdlib-license].


## Copyright

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

</section>

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[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules

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

[uniform-distribution]: https://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29

[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

[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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