npm package: @stdlib/stats-array-meankbn
Description: Calculate the arithmetic mean of an array using an improved Kahan–Babuška algorithm.
Author: The Stdlib Authors
Latest version: 0.1.1

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# meankbn

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

> Calculate the [arithmetic mean][arithmetic-mean] of an array using an improved Kahan–Babuška algorithm.

<section class="intro">

</section>

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<section class="installation">

## Installation

```bash
npm install @stdlib/stats-array-meankbn
```

</section>

<section class="usage">

## Usage

```javascript
var meankbn = require( '@stdlib/stats-array-meankbn' );
```

#### meankbn( x )

Computes the [arithmetic mean][arithmetic-mean] of an array using an improved Kahan–Babuška algorithm.

```javascript
var x = [ 1.0, -2.0, 2.0 ];

var v = meankbn( x );
// returns ~0.3333
```

The function has the following parameters:

-   **x**: input array.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If provided an empty array, the function returns `NaN`.
-   The function supports array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array-base/accessor`][@stdlib/array/base/accessor]).

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var meankbn = require( '@stdlib/stats-array-meankbn' );

var x = discreteUniform( 10, -50, 50, {
    'dtype': 'float64'
});
console.log( x );

var v = meankbn( x );
console.log( v );
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

</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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[test-image]: https://github.com/stdlib-js/stats-array-meankbn/actions/workflows/test.yml/badge.svg?branch=v0.1.1
[test-url]: https://github.com/stdlib-js/stats-array-meankbn/actions/workflows/test.yml?query=branch:v0.1.1

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-array-meankbn/main.svg
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[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-array-meankbn/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-array-meankbn/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-array-meankbn/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-array-meankbn/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-array-meankbn/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-array-meankbn/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-array-meankbn/blob/main/branches.md

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-array-meankbn/main/LICENSE

[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean

[@stdlib/array/base/accessor]: https://www.npmjs.com/package/@stdlib/array-base-accessor

</section>

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