About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

Discrete Uniform

Discrete uniform distribution constructor.

Installation

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 available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md 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

var DiscreteUniform = require( '@stdlib/stats-base-dists-discrete-uniform-ctor' );

DiscreteUniform( [a, b] )

Returns a discrete uniform distribution object.

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.

var discreteUniform = new DiscreteUniform( 2, 4 );

var mu = discreteUniform.mean;
// returns 3.0

---

discreteUniform

A discrete uniform 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.

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.

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.

var discreteUniform = new DiscreteUniform( 4, 12 );

var entropy = discreteUniform.entropy;
// returns ~2.197

DiscreteUniform.prototype.kurtosis

Returns the excess kurtosis.

var discreteUniform = new DiscreteUniform( 4, 12 );

var kurtosis = discreteUniform.kurtosis;
// returns -1.23

DiscreteUniform.prototype.mean

Returns the expected value.

var discreteUniform = new DiscreteUniform( 4, 12 );

var mu = discreteUniform.mean;
// returns 8.0

DiscreteUniform.prototype.median

Returns the median.

var discreteUniform = new DiscreteUniform( 4, 12 );

var median = discreteUniform.median;
// returns 8.0

DiscreteUniform.prototype.skewness

Returns the skewness.

var discreteUniform = new DiscreteUniform( 4, 12 );

var skewness = discreteUniform.skewness;
// returns 0.0

DiscreteUniform.prototype.stdev

Returns the standard deviation.

var discreteUniform = new DiscreteUniform( 4, 12 );

var s = discreteUniform.stdev;
// returns ~2.582

DiscreteUniform.prototype.variance

Returns the variance.

var discreteUniform = new DiscreteUniform( 4, 12 );

var s2 = discreteUniform.variance;
// returns ~6.667

---

Methods

DiscreteUniform.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

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).

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).

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).

var discreteUniform = new DiscreteUniform( 2, 4 );

var y = discreteUniform.pmf( 3, 0 );
// returns ~0.333

DiscreteUniform.prototype.quantile( p )

Evaluates the quantile function at probability p.

var discreteUniform = new DiscreteUniform( 2, 4 );

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

y = discreteUniform.quantile( 1.9 );
// returns NaN

---

Examples

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, 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, see the main project repository.

Community

---

License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.