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Compute the mean error (ME) incrementally.
The mean error is defined as
To use in Observable,
incrme = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-incr-me@umd/browser.js' )To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var incrme = require( 'path/to/vendor/umd/stats-incr-me/index.js' )To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-incr-me@umd/browser.js"></script>If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.incrme;
})();
</script>Returns an accumulator function which incrementally computes the mean error.
var accumulator = incrme();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- 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. - 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.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-incr-me@umd/browser.js"></script>
<script type="text/javascript">
(function () {
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() );
})();
</script>
</body>
</html>@stdlib/stats-incr/mae: compute the mean absolute error (MAE) incrementally.@stdlib/stats-incr/mean: compute an arithmetic mean incrementally.@stdlib/stats-incr/mme: compute a moving mean error (ME) incrementally.
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.
See LICENSE.
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