incrme

Compute the mean error (ME) incrementally.

The mean error is defined as

Usage

var incrme = require( '@stdlib/stats/incr/me' );

incrme()

Returns an accumulator function which incrementally computes the mean error.

var accumulator = incrme();

accumulator( [x, y] )

If provided input values x and y, the accumulator function returns an updated mean error. If not provided input values x and y, the accumulator function returns the current mean error.

var accumulator = incrme();

var m = accumulator( 2.0, 3.0 );
// returns 1.0

m = accumulator( -1.0, -4.0 );
// returns -1.0

m = accumulator( -3.0, 5.0 );
// returns 2.0

m = accumulator();
// returns 2.0

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.
Be careful when interpreting the mean error as errors can cancel. This stated, that errors can cancel makes the mean error suitable for measuring the bias in forecasts.
Warning: the mean error is scale-dependent and, thus, the measure should not be used to make comparisons between datasets having different scales.

Examples

var randu = require( '@stdlib/random/base/randu' );
var incrme = require( '@stdlib/stats/incr/me' );

var accumulator;
var v1;
var v2;
var i;

// Initialize an accumulator:
accumulator = incrme();

// For each simulated datum, update the mean 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() );