# incrmmeanstdev > Compute a moving [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][standard-deviation] incrementally.
For a window of size `W`, the [arithmetic mean][arithmetic-mean] is defined as
Equation for the arithmetic mean.
and the [corrected sample standard deviation][standard-deviation] is defined as
Equation for the corrected sample standard deviation.
## Usage ```javascript var incrmmeanstdev = require( '@stdlib/stats/incr/mmeanstdev' ); ``` #### incrmmeanstdev( \[out,] window ) Returns an accumulator `function` which incrementally computes a moving [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][standard-deviation]. The `window` parameter defines the number of values over which to compute the moving [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][standard-deviation]. ```javascript var accumulator = incrmmeanstdev( 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 = incrmmeanstdev( 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 = incrmmeanstdev( 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, ~0.71 ] 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, ~5.29 ] out = accumulator( -5.0 ); // [3.0, -7.0, -5.0] // returns [ -3.0, ~5.29 ] out = accumulator(); // returns [ -3.0, ~5.29 ] ```
## 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. - 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.
## Examples ```javascript var randu = require( '@stdlib/random/base/randu' ); var Float64Array = require( '@stdlib/array/float64' ); var ArrayBuffer = require( '@stdlib/array/buffer' ); var incrmmeanstdev = require( '@stdlib/stats/incr/mmeanstdev' ); var offset; var acc; var buf; var out; var ms; 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( incrmmeanstdev( out, 5 ) ); } // Simulate data and update the moving sample means and standard deviations... 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\tStDev' ); for ( i = 0; i < N; i++ ) { ms = acc[ i ](); console.log( '%d\t%d', ms[ 0 ].toFixed( 3 ), ms[ 1 ].toFixed( 3 ) ); } ```