solving eslint issue in README.js

Author: gkbishnoi07

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

@@ -69,13 +69,13 @@ s2 = accumulator( -5.0 ); // [2.0, NaN, -5.0]
 
 // Window begins sliding...
 s2 = accumulator( 3.0 ); // [NaN, -5.0, 3.0]
-// returns 32.0
+// returns 19.0
 
 s2 = accumulator( NaN ); // [-5.0, 3.0, NaN]
-// returns 32.0
+// returns 19.0
 
 s2 = accumulator();
-// returns 32.0
+// returns 19.0
 ```
 
 </section>

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

@@ -80,7 +80,7 @@ function incrnanmvariance( W, mean ) {
 		throw new TypeError( format( 'invalid argument. Must provide a positive integer. Value: `%s`.', W ) );
 	}
 
-	buf = new Array( W );
+	buf = [];
 	n = W - 1;
 	M2 = 0.0;
 	i = -1;
@@ -105,9 +105,6 @@ function incrnanmvariance( W, mean ) {
 	* @returns {(number|null)} unbiased sample variance or null
 	*/
 	function accumulator1( x ) {
-		var k;
-		var v;
-
 		if ( arguments.length === 0 ) {
 			if ( N === 0 ) {
 				return null;
@@ -116,60 +113,72 @@ function incrnanmvariance( W, mean ) {
 				return 0.0;
 			}
 			if ( N < W ) {
-				return M2 / (N-1);
+				return M2 / ( N - 1 );
 			}
 			return M2 / n;
 		}
 
-		// If incoming value is NaN, ignore it:
 		if ( isnan( x ) ) {
-			return ( N === 0 ) ? null : ( N === 1 ) ? 0.0 : ( N < W ) ? M2 / (N-1) : M2 / n;
+			if ( N === 0 ) {
+				return null;
+			}
+			if ( N === 1 ) {
+				return 0.0;
+			}
+			if ( N < W ) {
+				return M2 / ( N - 1 );
+			}
+			return M2 / n;
 		}
 
+
 		// Update the index for managing the circular buffer:
-		i = (i+1) % W;
+		i = ( i+1 ) % W;
 
 		// Case: initial window...
 		if ( N < W ) {
-			buf[ i ] = x; // update buffer
+			if ( N < W ) {
+				buf.push( x );
+			} else {
+				buf[ i ] = x;
+			}
 			N += 1;
 			delta = x - mu;
 			mu += delta / N;
-			M2 += delta * (x - mu);
+			M2 += delta * ( x - mu );
 			if ( N === 1 ) {
 				return 0.0;
 			}
-			return M2 / (N-1);
+			return M2 / ( N-1 );
 		}
 
 		// Case: N = W = 1
-		else if ( N === 1 ) {
+		if (N === 1) {
 			M2 = 0.0;
 			return M2;
 		}
 
 		// Case: outgoing value is NaN, which we need to simply replace without affecting the variance
-		else if ( isnan( buf[ i ] ) ) {
-			buf[ i ] = x;
-			// When replacing NaN with a value, we need to update M2 with the squared difference from mean
+		if (isnan(buf[i])) {
+			buf[i] = x;
+
+			// When replacing NaN with a value, update M2 with the squared difference from the mean
 			M2 += (x - mu) * (x - mu);
 			return M2 / n;
 		}
 
 		// Case: standard update when neither incoming nor outgoing values are NaN
-		else {
-			tmp = buf[ i ];
-			delta = x - tmp;
-			d1 = tmp - mu;
-			mu += delta / N;
-			d2 = x - mu;
-			M2 += delta * (d1 + d2);
-		}
-
-		buf[ i ] = x;
+		tmp = buf[i];
+		delta = x - tmp;
+		d1 = tmp - mu;
+		mu += delta / N;
+		d2 = x - mu;
+		M2 += delta * (d1 + d2);
+
+		buf[i] = x;
 		return M2 / n;
 	}
-
+	
 	/**
 	* If provided a value, the accumulator function returns an updated unbiased sample variance, ignoring NaN values. If not provided a value, the accumulator function returns the current unbiased sample variance.
 	*
@@ -178,8 +187,6 @@ function incrnanmvariance( W, mean ) {
 	* @returns {(number|null)} unbiased sample variance or null
 	*/
 	function accumulator2( x ) {
-		var k;
-
 		if ( arguments.length === 0 ) {
 			if ( N === 0 ) {
 				return null;
@@ -200,7 +207,11 @@ function incrnanmvariance( W, mean ) {
 
 		// Case: initial window...
 		if ( N < W ) {
-			buf[ i ] = x; // update buffer
+			if ( N < W ) {
+				buf.push( x );
+			} else {
+				buf[ i ] = x;
+			}
 			N += 1;
 			delta = x - mu;
 			M2 += delta * delta;
@@ -210,6 +221,7 @@ function incrnanmvariance( W, mean ) {
 		// Case: outgoing value is NaN, which we need to simply replace without affecting the variance
 		else if ( isnan( buf[ i ] ) ) {
 			buf[ i ] = x;
+
 			// Add the squared difference between the new value and mean
 			M2 += (x - mu) * (x - mu);
 			return M2 / W;
@@ -218,8 +230,10 @@ function incrnanmvariance( W, mean ) {
 		// Case: standard update when neither incoming nor outgoing values are NaN
 		else {
 			tmp = buf[ i ];
+
 			// Remove the contribution of the outgoing value
 			M2 -= (tmp - mu) * (tmp - mu);
+
 			// Add the contribution of the incoming value
 			M2 += (x - mu) * (x - mu);
 		}