@stdlib/stats-incr-mmeanvar
v0.2.3TypeScript
Compute a moving arithmetic mean and unbiased sample variance incrementally.
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Published by The Stdlib Authors
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incrmmeanvar
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> Compute a moving [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance] incrementally.
For a window of size W, the [arithmetic mean][arithmetic-mean] is defined as
and the [unbiased sample variance][sample-variance] is defined as
Installation
``bash`
npm install @stdlib/stats-incr-mmeanvar
Usage
`javascript`
var incrmmeanvar = require( '@stdlib/stats-incr-mmeanvar' );
#### incrmmeanvar( \[out,] window )
Returns an accumulator function which incrementally computes a moving [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance]. The window parameter defines the number of values over which to compute the moving [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance].
`javascript`
var accumulator = incrmmeanvar( 3 );
By default, the returned accumulator function returns the accumulated values as a two-element array. To avoid unnecessary memory allocation, the function supports providing an output (destination) object.
`javascript
var Float64Array = require( '@stdlib/array-float64' );
var accumulator = incrmmeanvar( new Float64Array( 2 ), 3 );
`
#### accumulator( \[x] )
If provided an input value x, the accumulator function returns updated accumulated values. If not provided an input value x, the accumulator function returns the current accumulated values.
`javascript
var accumulator = incrmmeanvar( 3 );
var out = accumulator();
// returns null
// Fill the window...
out = accumulator( 2.0 ); // [2.0]
// returns [ 2.0, 0.0 ]
out = accumulator( 1.0 ); // [2.0, 1.0]
// returns [ 1.5, 0.5 ]
out = accumulator( 3.0 ); // [2.0, 1.0, 3.0]
// returns [ 2.0, 1.0 ]
// Window begins sliding...
out = accumulator( -7.0 ); // [1.0, 3.0, -7.0]
// returns [ -1.0, 28.0 ]
out = accumulator( -5.0 ); // [3.0, -7.0, -5.0]
// returns [ -3.0, 28.0 ]
out = accumulator();
// returns [ -3.0, 28.0 ]
`
Notes
- Input values are not type checked. If provided NaN, the accumulated values are 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.W
- As 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.
Examples
`javascript
var randu = require( '@stdlib/random-base-randu' );
var Float64Array = require( '@stdlib/array-float64' );
var ArrayBuffer = require( '@stdlib/array-buffer' );
var incrmmeanvar = require( '@stdlib/stats-incr-mmeanvar' );
var offset;
var acc;
var buf;
var out;
var mv;
var N;
var v;
var i;
var j;
// Define the number of accumulators:
N = 5;
// Create an array buffer for storing accumulator output:
buf = new ArrayBuffer( N28 ); // 8 bytes per element
// Initialize accumulators:
acc = [];
for ( i = 0; i < N; i++ ) {
// Compute the byte offset:
offset = i 2 8; // stride=2, bytes_per_element=8
// Create a new view for storing accumulated values:
out = new Float64Array( buf, offset, 2 );
// Initialize an accumulator which will write results to the view:
acc.push( incrmmeanvar( out, 5 ) );
}
// Simulate data and update the moving sample means and variances...
for ( i = 0; i < 100; i++ ) {
for ( j = 0; j < N; j++ ) {
v = randu() 100.0 (j+1);
acc j ;
}
}
// Print the final results:
console.log( 'Mean\tVariance' );
for ( i = 0; i < N; i++ ) {
mv = acc[ i ]();
console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) );
}
`
*
See Also
- [@stdlib/stats-incr/meanvar][@stdlib/stats/incr/meanvar]: compute an arithmetic mean and unbiased sample variance incrementally.
- [@stdlib/stats-incr/mmean][@stdlib/stats/incr/mmean]: compute a moving arithmetic mean incrementally.
- [@stdlib/stats-incr/mmeanstdev][@stdlib/stats/incr/mmeanstdev]: compute a moving arithmetic mean and corrected sample standard deviation incrementally.
- [@stdlib/stats-incr/mvariance][@stdlib/stats/incr/mvariance]: compute a moving unbiased sample variance incrementally.
*
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 © 2016-2026. The Stdlib [Authors][stdlib-authors].
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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-mmeanvar/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-incr-mmeanvar/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-incr-mmeanvar/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-incr-mmeanvar/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-incr-mmeanvar/tree/esm
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-incr-mmeanvar/main/LICENSE
[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
[sample-variance]: https://en.wikipedia.org/wiki/Variance
[@stdlib/stats/incr/meanvar]: https://www.npmjs.com/package/@stdlib/stats-incr-meanvar
[@stdlib/stats/incr/mmean]: https://www.npmjs.com/package/@stdlib/stats-incr-mmean
[@stdlib/stats/incr/mmeanstdev]: https://www.npmjs.com/package/@stdlib/stats-incr-mmeanstdev
[@stdlib/stats/incr/mvariance]: https://www.npmjs.com/package/@stdlib/stats-incr-mvariance