npm package: @stdlib/stats-incr-mvariance
Description: Compute a moving unbiased sample variance incrementally.
Author: The Stdlib Authors
Latest version: 0.2.3

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<details>
  <summary>
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  <p>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.</p>
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</details>

# incrmvariance

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

> Compute a moving [unbiased sample variance][sample-variance] incrementally.

<section class="intro">

For a window of size `W`, the [unbiased sample variance][sample-variance] is defined as

<!-- <equation class="equation" label="eq:unbiased_sample_variance" align="center" raw="s^2 = \frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2" alt="Equation for the unbiased sample variance."> -->

<div class="equation" align="center" data-raw-text="s^2 = \frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2" data-equation="eq:unbiased_sample_variance">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/mvariance/docs/img/equation_unbiased_sample_variance.svg" alt="Equation for the unbiased sample variance.">
    <br>
</div>

<!-- </equation> -->

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-incr-mvariance
```

</section>

<section class="usage">

## Usage

```javascript
var incrmvariance = require( '@stdlib/stats-incr-mvariance' );
```

#### incrmvariance( window\[, mean] )

Returns an accumulator `function` which incrementally computes a moving [unbiased sample variance][sample-variance]. The `window` parameter defines the number of values over which to compute the moving [unbiased sample variance][sample-variance].

```javascript
var accumulator = incrmvariance( 3 );
```

If the mean is already known, provide a `mean` argument.

```javascript
var accumulator = incrmvariance( 3, 5.0 );
```

#### accumulator( \[x] )

If provided an input value `x`, the accumulator function returns an updated [unbiased sample variance][sample-variance]. If not provided an input value `x`, the accumulator function returns the current [unbiased sample variance][sample-variance].

```javascript
var accumulator = incrmvariance( 3 );

var s2 = accumulator();
// returns null

// Fill the window...
s2 = accumulator( 2.0 ); // [2.0]
// returns 0.0

s2 = accumulator( 1.0 ); // [2.0, 1.0]
// returns 0.5

s2 = accumulator( 3.0 ); // [2.0, 1.0, 3.0]
// returns 1.0

// Window begins sliding...
s2 = accumulator( -7.0 ); // [1.0, 3.0, -7.0]
// returns 28.0

s2 = accumulator( -5.0 ); // [3.0, -7.0, -5.0]
// returns 28.0

s2 = accumulator();
// returns 28.0
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for **at least** `W-1` future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
-   As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var randu = require( '@stdlib/random-base-randu' );
var incrmvariance = require( '@stdlib/stats-incr-mvariance' );

var accumulator;
var v;
var i;

// Initialize an accumulator:
accumulator = incrmvariance( 5 );

// For each simulated datum, update the moving unbiased sample variance...
for ( i = 0; i < 100; i++ ) {
    v = randu() * 100.0;
    accumulator( v );
}
console.log( accumulator() );
```

</section>

<!-- /.examples -->

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

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/stats-incr/mmean`][@stdlib/stats/incr/mmean]</span><span class="delimiter">: </span><span class="description">compute a moving arithmetic mean incrementally.</span>
-   <span class="package-name">[`@stdlib/stats-incr/mstdev`][@stdlib/stats/incr/mstdev]</span><span class="delimiter">: </span><span class="description">compute a moving corrected sample standard deviation incrementally.</span>
-   <span class="package-name">[`@stdlib/stats-incr/msummary`][@stdlib/stats/incr/msummary]</span><span class="delimiter">: </span><span class="description">compute a moving statistical summary incrementally.</span>
-   <span class="package-name">[`@stdlib/stats-incr/variance`][@stdlib/stats/incr/variance]</span><span class="delimiter">: </span><span class="description">compute an unbiased sample variance incrementally.</span>

</section>

<!-- /.related -->

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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>

<!-- /.stdlib -->

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[npm-url]: https://npmjs.org/package/@stdlib/stats-incr-mvariance

[test-image]: https://github.com/stdlib-js/stats-incr-mvariance/actions/workflows/test.yml/badge.svg?branch=v0.2.3
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[stdlib]: https://github.com/stdlib-js/stdlib

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[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-incr-mvariance/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-incr-mvariance/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-incr-mvariance/tree/umd
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[esm-url]: https://github.com/stdlib-js/stats-incr-mvariance/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-incr-mvariance/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-incr-mvariance/blob/main/branches.md

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

[sample-variance]: https://en.wikipedia.org/wiki/Variance

<!-- <related-links> -->

[@stdlib/stats/incr/mmean]: https://www.npmjs.com/package/@stdlib/stats-incr-mmean

[@stdlib/stats/incr/mstdev]: https://www.npmjs.com/package/@stdlib/stats-incr-mstdev

[@stdlib/stats/incr/msummary]: https://www.npmjs.com/package/@stdlib/stats-incr-msummary

[@stdlib/stats/incr/variance]: https://www.npmjs.com/package/@stdlib/stats-incr-variance

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</section>

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