## Usage ```javascript var incrmmaape = require( '@stdlib/stats/incr/mmaape' ); ``` #### incrmmaape( window ) Returns an accumulator `function` which incrementally computes a moving [mean arctangent absolute percentage error][@kim:2016a]. The `window` parameter defines the number of values over which to compute the moving [mean arctangent absolute percentage error][@kim:2016a]. ```javascript var accumulator = incrmmaape( 3 ); ``` #### accumulator( \[f, a] ) If provided input values `f` and `a`, the accumulator function returns an updated [mean arctangent absolute percentage error][@kim:2016a]. If not provided input values `f` and `a`, the accumulator function returns the current [mean arctangent absolute percentage error][@kim:2016a]. ```javascript var accumulator = incrmmaape( 3 ); var m = accumulator(); // returns null // Fill the window... m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)] // returns ~0.32 m = accumulator( 1.0, 4.0 ); // [(2.0,3.0), (1.0,4.0)] // returns ~0.48 m = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (1.0,4.0), (3.0,9.0)] // returns ~0.52 // Window begins sliding... m = accumulator( 7.0, 3.0 ); // [(1.0,4.0), (3.0,9.0), (7.0,3.0)] // returns ~0.72 m = accumulator( 5.0, 3.0 ); // [(3.0,9.0), (7.0,3.0), (5.0,3.0)] // returns ~0.70 m = accumulator(); // returns ~0.70 ```

## 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` (f,a) pairs 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. - Note that, unlike the [mean absolute percentage error][@stdlib/stats/incr/mape] (MAPE), the [mean arctangent absolute percentage error][@kim:2016a] is expressed in radians on the interval \[0,π/2].

## Examples ```javascript var randu = require( '@stdlib/random/base/randu' ); var incrmmaape = require( '@stdlib/stats/incr/mmaape' ); var accumulator; var v1; var v2; var i; // Initialize an accumulator: accumulator = incrmmaape( 5 ); // For each simulated datum, update the moving mean arctangent absolute percentage error... for ( i = 0; i < 100; i++ ) { v1 = ( randu()*100.0 ) + 50.0; v2 = ( randu()*100.0 ) + 50.0; accumulator( v1, v2 ); } console.log( accumulator() ); ```