incrmae

Compute the mean absolute error (MAE) incrementally.

The mean absolute error is defined as

Installation

npm install @stdlib/stats-incr-mae

Usage

var incrmae = require( '@stdlib/stats-incr-mae' );

incrmae()

Returns an accumulator function which incrementally computes the mean absolute error.

var accumulator = incrmae();

accumulator( [x, y] )

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

var accumulator = incrmae();

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

m = accumulator( -1.0, -4.0 );
// returns 2.0

m = accumulator( -3.0, 5.0 );
// returns 4.0

m = accumulator();
// returns 4.0

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.
• Warning: the mean absolute 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 incrmae = require( '@stdlib/stats-incr-mae' );

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

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

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

See Also

• @stdlib/stats-incr/mape: compute the mean absolute percentage error (MAPE) incrementally.
• @stdlib/stats-incr/me: compute the mean error (ME) incrementally.
• @stdlib/stats-incr/mean: compute an arithmetic mean incrementally.
• @stdlib/stats-incr/mmae: compute a moving mean absolute error (MAE) incrementally.

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.