time-to-botec/squiggle/node_modules/@stdlib/stats/iter/mmean

itermmean

Create an iterator which iteratively computes a moving arithmetic mean.

For a window of size W, the arithmetic mean is defined as

Usage

var itermmean = require( '@stdlib/stats/iter/mmean' );

itermmean( iterator, W )

Returns an iterator which iteratively computes a moving arithmetic mean. The W parameter defines the number of iterated values over which to compute the moving mean.

var array2iterator = require( '@stdlib/array/to-iterator' );

var arr = array2iterator( [ 2.0, 1.0, 3.0, -7.0, -5.0 ] );
var it = itermmean( arr, 3 );

// Fill the window...
var m = it.next().value; // [2.0]
// returns 2.0

m = it.next().value; // [2.0, 1.0]
// returns 1.5

m = it.next().value; // [2.0, 1.0, 3.0]
// returns 2.0

// Window begins sliding...
m = it.next().value; // [1.0, 3.0, -7.0]
// returns -1.0

m = it.next().value; // [3.0, -7.0, -5.0]
// returns -3.0

Notes

• If an iterated value is non-numeric (including NaN), the function returns NaN for at least W-1 future invocations. If non-numeric iterated values are possible, you are advised to provide an iterator which type checks and handles non-numeric values accordingly.
• 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 previously iterated values.

Examples

var runif = require( '@stdlib/random/iter/uniform' );
var itermmean = require( '@stdlib/stats/iter/mmean' );

// Create an iterator for generating uniformly distributed pseudorandom numbers:
var rand = runif( -10.0, 10.0, {
    'seed': 1234,
    'iter': 100
});

// Create an iterator for iteratively computing a moving arithmetic mean:
var it = itermmean( rand, 3 );

// Perform manual iteration...
var v;
while ( true ) {
    v = it.next();
    if ( typeof v.value === 'number' ) {
        console.log( 'Mean: %d', v.value );
    }
    if ( v.done ) {
        break;
    }
}