diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/nanmeanwd/README.md
index 40154a3583c8..6712e142e206 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/README.md
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/README.md
@@ -51,15 +51,14 @@ The [arithmetic mean][arithmetic-mean] is defined as
 var nanmeanwd = require( '@stdlib/stats/base/nanmeanwd' );
 ```
 
-#### nanmeanwd( N, x, stride )
+#### nanmeanwd( N, x, strideX )
 
-Computes the [arithmetic mean][arithmetic-mean] of a strided array `x`, ignoring `NaN` values and using Welford's algorithm.
+Computes the [arithmetic mean][arithmetic-mean] of a strided array, ignoring `NaN` values and using Welford's algorithm.
 
 ```javascript
 var x = [ 1.0, -2.0, NaN, 2.0 ];
-var N = x.length;
 
-var v = nanmeanwd( N, x, 1 );
+var v = nanmeanwd( x.length, x, 1 );
 // returns ~0.3333
 ```
 
@@ -67,62 +66,52 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ];
-var N = floor( x.length / 2 );
 
-var v = nanmeanwd( N, x, 2 );
+var v = nanmeanwd( 5, x, 2 );
 // returns 1.25
 ```
 
 Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
 
-<!-- eslint-disable stdlib/capitalized-comments -->
+<!-- eslint-disable stdlib/capitalized-comments, max-len -->
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
-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 N = floor( x0.length / 2 );
-
-var v = nanmeanwd( N, x1, 2 );
+var v = nanmeanwd( 5, x1, 2 );
 // returns 1.25
 ```
 
-#### nanmeanwd.ndarray( N, x, stride, offset )
+#### nanmeanwd.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
 
 ```javascript
 var x = [ 1.0, -2.0, NaN, 2.0 ];
-var N = x.length;
 
-var v = nanmeanwd.ndarray( N, x, 1, 0 );
+var v = nanmeanwd.ndarray( x.length, x, 1, 0 );
 // returns ~0.33333
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in the strided array starting from the second element
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
-var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ];
-var N = floor( x.length / 2 );
+var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ];
 
-var v = nanmeanwd.ndarray( N, x, 2, 1 );
+var v = nanmeanwd.ndarray( 5, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -135,6 +124,7 @@ var v = nanmeanwd.ndarray( N, x, 2, 1 );
 ## Notes
 
 -   If `N <= 0`, both functions return `NaN`.
+-   Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
 -   If every indexed element is `NaN`, both functions return `NaN`.
 -   Depending on the environment, the typed versions ([`dnanmeanwd`][@stdlib/stats/strided/dnanmeanwd], [`snanmeanwd`][@stdlib/stats/strided/snanmeanwd], etc.) are likely to be significantly more performant.
 
@@ -149,22 +139,19 @@ var v = nanmeanwd.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
 var nanmeanwd = require( '@stdlib/stats/base/nanmeanwd' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        x[ i ] = NaN;
-    } else {
-        x[ i ] = round( (randu()*100.0) - 50.0 );
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
     }
+    return uniform( -50.0, 50.0 );
 }
+
+var x = filledarrayBy( 10, 'float64', rand );
 console.log( x );
 
 var v = nanmeanwd( x.length, x, 1 );
@@ -215,6 +202,8 @@ console.log( v );
 
 [mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
 
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
 [@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
 
 [@vanreeken:1968a]: https://doi.org/10.1145/362929.362961
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.js
index 1fe4b2b90b16..d0ebebf545df 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.js
@@ -21,15 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
-var nanmeanwd = require( './../lib/nanmeanwd.js' );
+var nanmeanwd = require( './../lib/main.js' );
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -38,17 +53,7 @@ var nanmeanwd = require( './../lib/nanmeanwd.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		if ( randu() < 0.2 ) {
-			x.push( NaN );
-		} else {
-			x.push( ( randu()*20.0 ) - 10.0 );
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.ndarray.js
index acb529bf193e..e9c395419a34 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.ndarray.js
@@ -21,7 +21,9 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
@@ -30,6 +32,19 @@ var nanmeanwd = require( './../lib/ndarray.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -38,17 +53,7 @@ var nanmeanwd = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		if ( randu() < 0.2 ) {
-			x.push( NaN );
-		} else {
-			x.push( ( randu()*20.0 ) - 10.0 );
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/repl.txt
index 0e61d562bf57..786fe03ebce0 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/repl.txt
@@ -1,10 +1,10 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the arithmetic mean of a strided array, ignoring `NaN` values and
     using Welford's algorithm.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -21,8 +21,8 @@
     x: Array<number>|TypedArray
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length.
 
     Returns
     -------
@@ -36,22 +36,19 @@
     > {{alias}}( x.length, x, 1 )
     ~0.3333
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{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 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 4, x1, 2 )
     ~-0.3333
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the arithmetic mean of a strided array, ignoring `NaN` values and
     using Welford's algorithm and alternative indexing semantics.
 
@@ -67,10 +64,10 @@
     x: Array<number>|TypedArray
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -86,9 +83,8 @@
     ~0.3333
 
     // Using offset parameter:
-    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];
+    > {{alias}}.ndarray( 4, x, 2, 1 )
     ~-0.3333
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/index.d.ts
index a918980530e0..88685729d8a7 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/index.d.ts
@@ -20,7 +20,12 @@
 
 /// <reference types="@stdlib/types"/>
 
-import { NumericArray } from '@stdlib/types/array';
+import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
+
+/**
+* Input array.
+*/
+type InputArray = NumericArray | Collection<number> | AccessorArrayLike<number>;
 
 /**
 * Interface describing `nanmeanwd`.
@@ -31,7 +36,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns arithmetic mean
 	*
 	* @example
@@ -40,15 +45,15 @@ interface Routine {
 	* var v = nanmeanwd( x.length, x, 1 );
 	* // returns ~0.3333
 	*/
-	( N: number, x: NumericArray, stride: number ): number;
+	( N: number, x: InputArray, strideX: number ): number;
 
 	/**
 	* Computes the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns arithmetic mean
 	*
 	* @example
@@ -57,7 +62,7 @@ interface Routine {
 	* var v = nanmeanwd.ndarray( x.length, x, 1, 0 );
 	* // returns ~0.3333
 	*/
-	ndarray( N: number, x: NumericArray, stride: number, offset: number ): number;
+	ndarray( N: number, x: InputArray, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +70,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns arithmetic mean
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/test.ts
index 10289c4f0a9f..b87c7e3b737c 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/test.ts
@@ -16,6 +16,7 @@
 * limitations under the License.
 */
 
+import AccessorArray = require( '@stdlib/array/base/accessor' );
 import nanmeanwd = require( './index' );
 
 
@@ -26,6 +27,7 @@ import nanmeanwd = require( './index' );
 	const x = new Float64Array( 10 );
 
 	nanmeanwd( x.length, x, 1 ); // $ExpectType number
+	nanmeanwd( x.length, new AccessorArray( x ), 1 ); // $ExpectType number
 }
 
 // The compiler throws an error if the function is provided a first argument which is not a number...
@@ -85,6 +87,7 @@ import nanmeanwd = require( './index' );
 	const x = new Float64Array( 10 );
 
 	nanmeanwd.ndarray( x.length, x, 1, 0 ); // $ExpectType number
+	nanmeanwd.ndarray( x.length, new AccessorArray( x ), 1, 0 ); // $ExpectType number
 }
 
 // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/examples/index.js
index cede2a9664bf..ef0c792a36b2 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/examples/index.js
@@ -18,22 +18,19 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
 var nanmeanwd = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	if ( randu() < 0.2 ) {
-		x[ i ] = NaN;
-	} else {
-		x[ i ] = round( (randu()*100.0) - 50.0 );
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
 	}
+	return uniform( -50.0, 50.0 );
 }
+
+var x = filledarrayBy( 10, 'float64', rand );
 console.log( x );
 
 var v = nanmeanwd( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/nanmeanwd.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/accessors.js
similarity index 67%
rename from lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/nanmeanwd.js
rename to lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/accessors.js
index c9a582d2fac8..cc7270ab03cb 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/nanmeanwd.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/accessors.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
@@ -41,45 +41,52 @@
 * -   Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022).
 * -   van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961).
 *
+* @private
 * @param {PositiveInteger} N - number of indexed elements
-* @param {NumericArray} x - input array
-* @param {integer} stride - stride length
+* @param {Object} x - input array object
+* @param {Collection} x.data - input array data
+* @param {Array<Function>} x.accessors - array element accessors
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} arithmetic mean
 *
 * @example
-* var x = [ 1.0, -2.0, NaN, 2.0 ];
-* var N = x.length;
+* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+* var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
 *
-* var v = nanmeanwd( N, x, 1 );
-* // returns ~0.3333
+* var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
+*
+* var v = nanmeanwd( 5, arraylike2object( x ), 2, 1 );
+* // returns 1.25
 */
-function nanmeanwd( N, x, stride ) {
+function nanmeanwd( N, x, strideX, offsetX ) {
+	var xbuf;
+	var get;
 	var mu;
 	var ix;
 	var v;
 	var n;
 	var i;
 
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		ix = (1-N) * stride;
-	} else {
-		ix = 0;
+	// Cache reference to array data:
+	xbuf = x.data;
+
+	// Cache a reference to the element accessor:
+	get = x.accessors[ 0 ];
+
+	if ( N === 1 || strideX === 0 ) {
+		return get( xbuf, offsetX );
 	}
+	ix = offsetX;
 	mu = 0.0;
 	n = 0;
 	for ( i = 0; i < N; i++ ) {
-		v = x[ ix ];
+		v = get( xbuf, ix );
 		if ( v === v ) {
 			n += 1;
 			mu += ( v-mu ) / n;
 		}
-		ix += stride;
+		ix += strideX;
 	}
 	if ( n === 0 ) {
 		return NaN;
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/index.js
index 6da72316d09a..7485dfd0a1a6 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/index.js
@@ -27,25 +27,29 @@
 * var nanmeanwd = require( '@stdlib/stats/base/nanmeanwd' );
 *
 * var x = [ 1.0, -2.0, NaN, 2.0 ];
-* var N = x.length;
 *
-* var v = nanmeanwd( N, x, 1 );
+* var v = nanmeanwd( x.length, x, 1 );
 * // returns ~0.3333
 *
 * @example
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var nanmeanwd = require( '@stdlib/stats/base/nanmeanwd' );
 *
 * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ];
-* var N = floor( x.length / 2 );
 *
-* var v = nanmeanwd.ndarray( N, x, 2, 1 );
+* var v = nanmeanwd.ndarray( 5, x, 2, 1 );
 * // returns 1.25
 */
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'ndarray', ndarray );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/main.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/main.js
index 4164c067b1c2..5daf297b0daa 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/main.js
@@ -20,14 +20,29 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
-var nanmeanwd = require( './nanmeanwd.js' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
 var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
 
-setReadOnly( nanmeanwd, 'ndarray', ndarray );
+/**
+* Computes the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {NumericArray} x - input array
+* @param {integer} strideX - stride length
+* @returns {number} arithmetic mean
+*
+* @example
+* var x = [ 1.0, -2.0, NaN, 2.0 ];
+*
+* var v = nanmeanwd( x.length, x, 1 );
+* // returns ~0.3333
+*/
+function nanmeanwd( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
+}
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/ndarray.js
index b7a86bb5ca90..03715ffeb8eb 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/lib/ndarray.js
@@ -18,6 +18,12 @@
 
 'use strict';
 
+// MODULES //
+
+var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+var accessors = require( './accessors.js' );
+
+
 // MAIN //
 
 /**
@@ -43,22 +49,20 @@
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {NumericArray} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} arithmetic mean
 *
 * @example
-* var floor = require( '@stdlib/math/base/special/floor' );
+* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ];
 *
-* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ];
-* var N = floor( x.length / 2 );
-*
-* var v = nanmeanwd( N, x, 2, 1 );
+* var v = nanmeanwd( 5, x, 2, 1 );
 * // returns 1.25
 */
-function nanmeanwd( N, x, stride, offset ) {
+function nanmeanwd( N, x, strideX, offsetX ) {
 	var mu;
 	var ix;
+	var o;
 	var v;
 	var n;
 	var i;
@@ -66,10 +70,14 @@ function nanmeanwd( N, x, stride, offset ) {
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ offset ];
+	o = arraylike2object( x );
+	if ( o.accessorProtocol ) {
+		return accessors( N, o, strideX, offsetX );
+	}
+	if ( N === 1 || strideX === 0 ) {
+		return x[ offsetX ];
 	}
-	ix = offset;
+	ix = offsetX;
 	mu = 0.0;
 	n = 0;
 	for ( i = 0; i < N; i++ ) {
@@ -78,7 +86,7 @@ function nanmeanwd( N, x, stride, offset ) {
 			n += 1;
 			mu += ( v-mu ) / n;
 		}
-		ix += stride;
+		ix += strideX;
 	}
 	if ( n === 0 ) {
 		return NaN;
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.nanmeanwd.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.nanmeanwd.js
index 9bcbf40660ac..7ff7ddb837f3 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.nanmeanwd.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.nanmeanwd.js
@@ -21,10 +21,10 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
 var Float64Array = require( '@stdlib/array/float64' );
-var nanmeanwd = require( './../lib/nanmeanwd.js' );
+var nanmeanwd = require( './../lib/main.js' );
 
 
 // TESTS //
@@ -62,6 +62,28 @@ tape( 'the function calculates the arithmetic mean of a strided array', function
 	t.end();
 });
 
+tape( 'the function calculates the arithmetic mean of a strided array (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 1 );
+	t.strictEqual( v, 0.5, 'returns expected value' );
+
+	x = [ -4.0, NaN ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 1 );
+	t.strictEqual( v, -4.0, 'returns expected value' );
+
+	x = [ NaN, NaN ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
 	var x;
 	var v;
@@ -77,6 +99,21 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	t.end();
 });
 
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = nanmeanwd( 0, toAccessorArray( x ), 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = nanmeanwd( -1, toAccessorArray( x ), 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'if provided an `N` parameter equal to `1`, the function returns the first element', function test( t ) {
 	var x;
 	var v;
@@ -89,8 +126,19 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 	t.end();
 });
 
+tape( 'if provided an `N` parameter equal to `1`, the function returns the first element (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = nanmeanwd( 1, toAccessorArray( x ), 1 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -107,15 +155,36 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		NaN
 	];
 
-	N = floor( x.length / 2 );
-	v = nanmeanwd( N, x, 2 );
+	v = nanmeanwd( 5, x, 2 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a `stride` parameter (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0,
+		NaN,  // 4
+		NaN
+	];
+
+	v = nanmeanwd( 5, toAccessorArray( x ), 2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -132,8 +201,30 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		NaN
 	];
 
-	N = floor( x.length / 2 );
-	v = nanmeanwd( N, x, -2 );
+	v = nanmeanwd( 5, x, -2 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 4
+		2.0,
+		2.0,  // 3
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 1
+		2.0,
+		NaN,  // 0
+		NaN
+	];
+
+	v = nanmeanwd( 5, toAccessorArray( x ), -2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -151,10 +242,21 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 	t.end();
 });
 
+tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 0 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -172,9 +274,35 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = nanmeanwd( N, x1, 2 );
+	v = nanmeanwd( 5, x1, 2 );
+	t.strictEqual( v, 1.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports view offsets (accessors)', function test( t ) {
+	var x0;
+	var x1;
+	var v;
+
+	x0 = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0,
+		NaN,  // 4
+		NaN
+	]);
+
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+	v = nanmeanwd( 5, toAccessorArray( x1 ), 2 );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.ndarray.js
index a6184badf47c..3c6e924e40ea 100644
--- a/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/nanmeanwd/test/test.ndarray.js
@@ -21,8 +21,8 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
 var nanmeanwd = require( './../lib/ndarray.js' );
 
 
@@ -61,6 +61,28 @@ tape( 'the function calculates the arithmetic mean of a strided array', function
 	t.end();
 });
 
+tape( 'the function calculates the arithmetic mean of a strided array (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( v, 0.5, 'returns expected value' );
+
+	x = [ -4.0, NaN ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( v, -4.0, 'returns expected value' );
+
+	x = [ NaN, NaN ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
 	var x;
 	var v;
@@ -76,6 +98,21 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	t.end();
 });
 
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = nanmeanwd( 0, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = nanmeanwd( -1, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'if provided an `N` parameter equal to `1`, the function returns the first indexed element', function test( t ) {
 	var x;
 	var v;
@@ -88,8 +125,19 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 	t.end();
 });
 
+tape( 'if provided an `N` parameter equal to `1`, the function returns the first indexed element (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = nanmeanwd( 1, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -106,15 +154,36 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		NaN
 	];
 
-	N = floor( x.length / 2 );
-	v = nanmeanwd( N, x, 2, 0 );
+	v = nanmeanwd( 5, x, 2, 0 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a `stride` parameter (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0,
+		NaN,  // 4
+		NaN
+	];
+
+	v = nanmeanwd( 5, toAccessorArray( x ), 2, 0 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,8 +200,30 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		NaN
 	];
 
-	N = floor( x.length / 2 );
-	v = nanmeanwd( N, x, -2, 8 );
+	v = nanmeanwd( 5, x, -2, 8 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 4
+		2.0,
+		2.0,  // 3
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 1
+		2.0,
+		NaN,  // 0
+		NaN
+	];
+
+	v = nanmeanwd( 5, toAccessorArray( x ), -2, 8 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -150,8 +241,19 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 	t.end();
 });
 
+tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = nanmeanwd( x.length, toAccessorArray( x ), 0, 0 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -167,9 +269,31 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		NaN,
 		NaN   // 4
 	];
-	N = floor( x.length / 2 );
 
-	v = nanmeanwd( N, x, 2, 1 );
+	v = nanmeanwd( 5, x, 2, 1 );
+	t.strictEqual( v, 1.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports an `offset` parameter (accessors)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		NaN,
+		NaN   // 4
+	];
+
+	v = nanmeanwd( 5, toAccessorArray( x ), 2, 1 );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();