# incrmape > Compute the [mean absolute percentage error][mean-absolute-percentage-error] (MAPE) incrementally.
The [mean absolute percentage error][mean-absolute-percentage-error] is defined as
Equation for the mean absolute percentage error.
where `f_i` is the forecast value and `a_i` is the actual value.
## Usage ```javascript var incrmape = require( '@stdlib/stats/incr/mape' ); ``` #### incrmape() Returns an accumulator `function` which incrementally computes the [mean absolute percentage error][mean-absolute-percentage-error]. ```javascript var accumulator = incrmape(); ``` #### accumulator( \[f, a] ) If provided input values `f` and `a`, the accumulator function returns an updated [mean absolute percentage error][mean-absolute-percentage-error]. If not provided input values `f` and `a`, the accumulator function returns the current [mean absolute percentage error][mean-absolute-percentage-error]. ```javascript var accumulator = incrmape(); var m = accumulator( 2.0, 3.0 ); // returns ~33.33 m = accumulator( 1.0, 4.0 ); // returns ~54.17 m = accumulator( 3.0, 5.0 ); // returns ~49.44 m = accumulator(); // returns ~49.44 ```
## 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 **all** 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. - **Warning**: the [mean absolute percentage error][mean-absolute-percentage-error] has several shortcomings: - The measure is **not** suitable for intermittent demand patterns (i.e., when `a_i` is `0`). - The [mean absolute percentage error][mean-absolute-percentage-error] is not symmetrical, as the measure cannot exceed 100% for forecasts which are too "low" and has no limit for forecasts which are too "high". - When used to compare the accuracy of forecast models (e.g., predicting demand), the measure is biased toward forecasts which are too low.
## Examples ```javascript var randu = require( '@stdlib/random/base/randu' ); var incrmape = require( '@stdlib/stats/incr/mape' ); var accumulator; var v1; var v2; var i; // Initialize an accumulator: accumulator = incrmape(); // For each simulated datum, update the mean 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() ); ```