Simplify implementation

kgryte · kgryte · commit b24542293386 · 2018-06-06T15:43:47.000-07:00
diff --git a/lib/node_modules/@stdlib/stats/incr/mae/lib/main.js b/lib/node_modules/@stdlib/stats/incr/mae/lib/main.js
@@ -21,28 +21,14 @@
 // MODULES //
 
 var abs = require( '@stdlib/math/base/special/abs' );
+var incrmean = require( '@stdlib/stats/incr/mean' );
 
 
 // MAIN //
 
 /**
 * Returns an accumulator function which incrementally computes the mean absolute error.
 *
-* ## Method
-*
-* -   This implementation uses [Welford's method][algorithms-variance] for efficient computation, which can be derived as follows
-*
-*     ```tex
-*     \begin{align*}
-*     \operatorname{MAE}_n &= \frac{1}{n} \sum_{i=0}^{n-1} |y_i - x_i| \\
-*           &= \frac{1}{n} \biggl(|y_{n-1} - x_{n-1}| + \sum_{i=0}^{n-2} |y_i - x_i|\biggr) \\
-*           &= \frac{1}{n} \biggl(|y_{n-1} - x_{n-1}| + (n-1)\operatorname{MAE}_{n-1}\biggr) \\
-*           &= \operatorname{MAE}_{n-1} + \frac{1}{n} \biggl(|y_{n-1} - x_{n-1}| - \operatorname{MAE}_{n-1}\biggr)
-*     \end{align*}
-*     ```
-*
-* [algorithms-variance]: https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
-*
 * @returns {Function} accumulator function
 *
 * @example
@@ -61,13 +47,7 @@ var abs = require( '@stdlib/math/base/special/abs' );
 * // returns 4.0
 */
 function incrmae() {
-	var delta;
-	var mu;
-	var N;
-
-	mu = 0.0;
-	N = 0;
-
+	var mean = incrmean();
 	return accumulator;
 
 	/**
@@ -80,15 +60,9 @@ function incrmae() {
 	*/
 	function accumulator( x, y ) {
 		if ( arguments.length === 0 ) {
-			if ( N === 0 ) {
-				return null;
-			}
-			return mu;
+			return mean();
 		}
-		N += 1;
-		delta = abs( y-x ) - mu;
-		mu += delta / N;
-		return mu;
+		return mean( abs( y-x ) );
 	}
 }
 
