chore: handling NaN elements

Author: Neerajpathak07

lib/node_modules/@stdlib/stats/base/dnanmeanors/README.md

@@ -75,9 +75,9 @@ The `N` and stride parameters determine which elements in the strided array are
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
-var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] );
+var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ] );
 
-var v = dnanmeanors( 4, x, 2 );
+var v = dnanmeanors( 5, x, 2 );
 // returns 1.25
 ```
 
@@ -88,10 +88,10 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
-var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var v = dnanmeanors( 4, x1, 2 );
+var v = dnanmeanors( 5, x1, 2 );
 // returns 1.25
 ```
 
@@ -117,9 +117,9 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
-var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
 
-var v = dnanmeanors.ndarray( 4, x, 2, 1 );
+var v = dnanmeanors.ndarray( 5, x, 2, 1 );
 // returns 1.25
 ```
 

lib/node_modules/@stdlib/stats/base/dnanmeanors/docs/repl.txt

@@ -37,14 +37,14 @@
     ~0.3333
 
     // Using `N` and stride parameters:
-    > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );
-    > {{alias}}( 3, x, 2 )
+    > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );
+    > {{alias}}( 4, x, 2 )
     ~0.3333
 
     // Using view offsets:
-    > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
+    > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > {{alias}}( 3, x1, 2 )
+    > {{alias}}( 4, x1, 2 )
     ~-0.3333
 
 
@@ -84,8 +84,8 @@
     ~0.3333
 
     // Using offset parameter:
-    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
-    > {{alias}}.ndarray( 3, x, 2, 1 )
+    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
+    > {{alias}}.ndarray( 4, x, 2, 1 )
     ~-0.3333
 
     See Also

lib/node_modules/@stdlib/stats/base/dnanmeanors/lib/index.js

@@ -36,9 +36,9 @@
 * var Float64Array = require( '@stdlib/array/float64' );
 * var dnanmeanors = require( '@stdlib/stats/base/dnanmeanors' );
 *
-* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
 *
-* var v = dnanmeanors.ndarray( 4, x, 2, 1 );
+* var v = dnanmeanors.ndarray( 5, x, 2, 1 );
 * // returns 1.25
 */
 

lib/node_modules/@stdlib/stats/base/dnanmeanors/lib/ndarray.js

@@ -32,9 +32,9 @@
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
-* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
 *
-* var v = dnanmeanors( 4, x, 2, 1 );
+* var v = dnanmeanors( 5, x, 2, 1 );
 * // returns 1.25
 */
 function dnanmeanors( N, x, strideX, offsetX ) {

lib/node_modules/@stdlib/stats/base/dnanmeanors/lib/ndarray.native.js

@@ -37,9 +37,9 @@ var addon = require( './../src/addon.node' );
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
-* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
 *
-* var v = dnanmeanors( 4, x, 2, 1 );
+* var v = dnanmeanors( 5, x, 2, 1 );
 * // returns 1.25
 */
 function dnanmeanors( N, x, strideX, offsetX ) {