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, wellwritten, studied, documented, tested, measured, and highquality 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!
incrmmeanvar
Compute a moving arithmetic mean and unbiased sample variance incrementally.
For a window of size W
, the arithmetic mean is defined as
and the unbiased sample variance is defined as
Installation
npm install @stdlib/statsincrmmeanvar
Usage
var incrmmeanvar = require( '@stdlib/statsincrmmeanvar' );
incrmmeanvar( [out,] window )
Returns an accumulator function
which incrementally computes a moving arithmetic mean and unbiased sample variance. The window
parameter defines the number of values over which to compute the moving arithmetic mean and unbiased sample variance.
var accumulator = incrmmeanvar( 3 );
By default, the returned accumulator function
returns the accumulated values as a twoelement array
. To avoid unnecessary memory allocation, the function supports providing an output (destination) object.
var Float64Array = require( '@stdlib/arrayfloat64' );
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.
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 areNaN
for at leastW1
future invocations. If nonnumeric 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 firstW1
returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
Examples
var randu = require( '@stdlib/randombaserandu' );
var Float64Array = require( '@stdlib/arrayfloat64' );
var ArrayBuffer = require( '@stdlib/arraybuffer' );
var incrmmeanvar = require( '@stdlib/statsincrmmeanvar' );
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( N*2*8 ); // 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 ]( v );
}
}
// 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/statsincr/meanvar
: compute an arithmetic mean and unbiased sample variance incrementally. 
@stdlib/statsincr/mmean
: compute a moving arithmetic mean incrementally. 
@stdlib/statsincr/mmeanstdev
: compute a moving arithmetic mean and corrected sample standard deviation incrementally. 
@stdlib/statsincr/mvariance
: compute a moving unbiased sample variance incrementally.
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 © 20162024. The Stdlib Authors.