chore: fixed linting and clean-up

Author: Girish-Garg

lib/node_modules/@stdlib/stats/incr/nanewstdev/README.md

@@ -20,7 +20,7 @@ limitations under the License.
 
 # incrnanewstdev
 
-> Compute an [exponentially weighted standard deviation][moving-average] incrementally.
+> Compute an [exponentially weighted standard deviation][moving-average] incrementally, ignoring `NaN` values.
 
 <section class="intro">
 
@@ -55,7 +55,7 @@ var incrnanewstdev = require( '@stdlib/stats/incr/nanewstdev' );
 
 #### incrnanewstdev( alpha )
 
-Returns an accumulator `function` which incrementally computes an [exponentially weighted standard deviation][moving-average], where `alpha` is a smoothing factor between `0` and `1`.
+Returns an accumulator `function` which incrementally computes an [exponentially weighted standard deviation][moving-average], where `alpha` is a smoothing factor between `0` and `1`, ignoring `NaN` values.
 
 ```javascript
 var accumulator = incrnanewstdev( 0.5 );
@@ -95,7 +95,7 @@ s = accumulator();
 
 ## Notes
 
--   Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, it will be **ignored** but you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
+-   Input values are **not** type checked.If non-numeric inputs are possible, but you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
 
 </section>
 
@@ -109,8 +109,8 @@ s = accumulator();
 
 ```javascript
 var randu = require( '@stdlib/random/base/randu' );
-var incrnanewstdev = require( './../lib' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var incrnanewstdev = require( '@stdlib/stats/incr/nanewstdev' );
 
 var accumulator;
 var s;

lib/node_modules/@stdlib/stats/incr/nanewstdev/benchmark/benchmark.js

@@ -21,7 +21,6 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
 var pkg = require( './../package.json' ).name;
 var incrnanewstdev = require( './../lib' );
 
@@ -55,7 +54,7 @@ bench( pkg+'::accumulator', function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		v = acc( randu() );
+		v = acc( i );
 		if ( v !== v ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/repl.txt

@@ -2,15 +2,12 @@
 {{alias}}( α )
     Returns an accumulator function which incrementally computes an
     exponentially weighted standard deviation, where α is a smoothing factor
-    between 0 and 1.
+    between 0 and 1, ignoring `NaN` values.
 
     If provided a value, the accumulator function returns an updated standard
     deviation. If not provided a value, the accumulator function returns the
     current standard deviation.
 
-    If provided `NaN` or a value which, when used in computations, results in
-    `NaN`, it will be ignored by accumulator function.
-
     Parameters
     ----------
     α: number

lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/index.d.ts

@@ -23,17 +23,13 @@
 /**
 * If provided a value, the accumulator function returns an updated standard deviation. If not provided a value, the accumulator function returns the current standard deviation.
 *
-* ## Notes
-*
-* -   If provided `NaN` or a value which, when used in computations, results in `NaN`, it will be ignored.
-*
 * @param x - value
 * @returns standard deviation or null
 */
 type accumulator = ( x?: number ) => number | null;
 
 /**
-* Returns an accumulator function which incrementally computes an exponentially weighted standard deviation.
+* Returns an accumulator function which incrementally computes an exponentially weighted standard deviation, ignoring `NaN` values.
 *
 * @param alpha - smoothing factor
 * @throws must be on the interval `[0,1]`
@@ -48,7 +44,7 @@ type accumulator = ( x?: number ) => number | null;
 * s = accumulator( 2.0 );
 * // returns 0.0
 *
-* s = accumulator( NaN ); // ignored
+* s = accumulator( NaN );
 * // returns 0.0
 *
 * s = accumulator( -5.0 );

lib/node_modules/@stdlib/stats/incr/nanewstdev/examples/index.js

@@ -19,8 +19,8 @@
 'use strict';
 
 var randu = require( '@stdlib/random/base/randu' );
-var incrnanewstdev = require( './../lib' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var incrnanewstdev = require( './../lib' );
 
 var accumulator;
 var s;
@@ -33,8 +33,8 @@ accumulator = incrnanewstdev( 0.5 );
 // For each simulated datum, update the exponentially weighted standard deviation...
 console.log( '\nValue\tStDev\n' );
 for ( i = 0; i < 100; i++ ) {
-	v = (randu() < 0.1) ? NaN : randu() * 100.0; // 10% chance of a NaN
+	v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; // 10% chance of a NaN
 	s = accumulator( v );
-	console.log( '%d\t%d', isnan(v) ? 'NaN' : v.toFixed( 4 ), s.toFixed( 4 ) );
+	console.log( '%d\t%d', ( isnan(v) ) ? 'NaN' : v.toFixed( 4 ), s.toFixed( 4 ) );
 }
 console.log( '\nFinal StDev: %d\n', accumulator() );

lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/index.js

@@ -19,7 +19,7 @@
 'use strict';
 
 /**
-* Compute an exponentially weighted standard deviation incrementally.
+* Compute an exponentially weighted standard deviation incrementally, ignoring `NaN` values.
 *
 * @module @stdlib/stats/incr/nanewstdev
 *
@@ -34,7 +34,7 @@
 * s = accumulator( 2.0 );
 * // returns 0.0
 *
-* s = accumulator( NaN ); // ignored
+* s = accumulator( NaN );
 * // returns 0.0
 *
 * s = accumulator( -5.0 );

lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/main.js

@@ -21,7 +21,8 @@
 // MODULES //
 
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var increwstdev = require('@stdlib/stats/incr/ewstdev');
+var increwstdev = require( '@stdlib/stats/incr/ewstdev' );
+
 
 // MAIN //
 
@@ -42,7 +43,7 @@ var increwstdev = require('@stdlib/stats/incr/ewstdev');
 * s = accumulator( 2.0 );
 * // returns 0.0
 *
-* s = accumulator( NaN ); // ignored
+* s = accumulator( NaN );
 * // returns 0.0
 *
 * s = accumulator( -5.0 );

lib/node_modules/@stdlib/stats/incr/nanewstdev/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@stdlib/stats/incr/nanewstdev",
   "version": "0.0.0",
-  "description": "Compute an exponentially weighted standard deviation incrementally.",
+  "description": "Compute an exponentially weighted standard deviation incrementally, ignoring `NaN` values.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",

lib/node_modules/@stdlib/stats/incr/nanewstdev/test/test.js

@@ -127,12 +127,12 @@ tape( 'the accumulator function incrementally computes an exponentially weighted
 		sqrt( (0.5*0.859375) + (0.25*pow( 3.0-3.125, 2 )) ), // m = 3.0625, s2 = 0.43359375
 		sqrt( (0.5*0.43359375) + (0.25*pow( 4.0-3.0625, 2 )) ) // m = 3.53125, s2 = 0.4365234375
 	];
-	actual = new Array( N );
+	actual = [];
 
 	acc = incrnanewstdev( 0.5 );
 
 	for ( i = 0; i < N; i++ ) {
-		actual[ i ] = acc( data[ i ] );
+		actual.push( acc( data[ i ] ) );
 	}
 	t.deepEqual( actual, expected, 'returns expected values' );
 	t.end();