5.0 KiB
5.0 KiB
incrmmaape
Compute a moving mean arctangent absolute percentage error (MAAPE) incrementally.
For a window of size W
, the mean arctangent absolute percentage error is defined as
where f_i
is the forecast value and a_i
is the actual value.
Usage
var incrmmaape = require( '@stdlib/stats/incr/mmaape' );
incrmmaape( window )
Returns an accumulator function
which incrementally computes a moving mean arctangent absolute percentage error. The window
parameter defines the number of values over which to compute the moving mean arctangent absolute percentage error.
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. If not provided input values f
and a
, the accumulator function returns the current mean arctangent absolute percentage error.
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 inNaN
, the accumulated value isNaN
for at leastW-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 firstW-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 (MAPE), the mean arctangent absolute percentage error is expressed in radians on the interval [0,π/2].
Examples
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() );
References
- Kim, Sungil, and Heeyoung Kim. 2016. "A new metric of absolute percentage error for intermittent demand forecasts." International Journal of Forecasting 32 (3): 669–79. doi:10.1016/j.ijforecast.2015.12.003.