@stdlib/stats-incr-mda v0.2.2
incrmda
Compute the mean directional accuracy (MDA) incrementally.
The mean directional accuracy is defined as
where f_i is the forecast value, a_i is the actual value, sgn(x) is the signum function, and δ is the Kronecker delta. 
Installation
npm install @stdlib/stats-incr-mdaUsage
var incrmda = require( '@stdlib/stats-incr-mda' );incrmda()
Returns an accumulator function which incrementally computes the mean directional accuracy.
var accumulator = incrmda();accumulator( [f, a] )
If provided input values f and a, the accumulator function returns an updated mean directional accuracy. If not provided input values f and a, the accumulator function returns the current mean directional accuracy.
var accumulator = incrmda();
var m = accumulator( 2.0, 3.0 );
// returns 1.0
m = accumulator( -1.0, 4.0 );
// returns 0.5
m = accumulator( -3.0, -2.0 );
// returns ~0.67
m = accumulator();
// returns ~0.67Notes
- Input values are not type checked. If provided NaNor a value which, when used in computations, results inNaN, the accumulated value isNaNfor 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.
Examples
var randu = require( '@stdlib/random-base-randu' );
var incrmda = require( '@stdlib/stats-incr-mda' );
var accumulator;
var v1;
var v2;
var i;
// Initialize an accumulator:
accumulator = incrmda();
// For each simulated datum, update the mean directional accuracy...
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/mmda: compute a moving mean directional accuracy (MDA) 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.