diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/README.md b/lib/node_modules/@stdlib/stats/base/varianceyc/README.md
index 1e4d0fe95ea4..a05b606f4f10 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/README.md
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/README.md
@@ -98,14 +98,14 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note,
 var varianceyc = require( '@stdlib/stats/base/varianceyc' );
 ```
 
-#### varianceyc( N, correction, x, stride )
+#### varianceyc( N, correction, x, strideX )
 
-Computes the [variance][variance] of a strided array `x` using a one-pass algorithm proposed by Youngs and Cramer.
+Computes the [variance][variance] of a strided array using a one-pass algorithm proposed by Youngs and Cramer.
 
 ```javascript
 var x = [ 1.0, -2.0, 2.0 ];
 
-var v = varianceyc( x.length, 1, x, 1 );
+var v = varianceyc( x.length, 1.0, x, 1 );
 // returns ~4.3333
 ```
 
@@ -114,17 +114,14 @@ The function has the following parameters:
 -   **N**: number of indexed elements.
 -   **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
 -   **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 [variance][variance] 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 [variance][variance] 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 ];
-var N = floor( x.length / 2 );
 
-var v = varianceyc( N, 1, x, 2 );
+var v = varianceyc( 4, 1.0, x, 2 );
 // returns 6.25
 ```
 
@@ -134,41 +131,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```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 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = varianceyc( N, 1, x1, 2 );
+var v = varianceyc( 4, 1.0, x1, 2 );
 // returns 6.25
 ```
 
-#### varianceyc.ndarray( N, correction, x, stride, offset )
+#### varianceyc.ndarray( N, correction, x, strideX, offsetX )
 
 Computes the [variance][variance] of a strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics.
 
 ```javascript
 var x = [ 1.0, -2.0, 2.0 ];
 
-var v = varianceyc.ndarray( x.length, 1, x, 1, 0 );
+var v = varianceyc.ndarray( x.length, 1.0, x, 1, 0 );
 // returns ~4.33333
 ```
 
 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 [variance][variance] 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 [variance][variance] for every other element in `x` 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 ];
-var N = floor( x.length / 2 );
 
-var v = varianceyc.ndarray( N, 1, x, 2, 1 );
+var v = varianceyc.ndarray( 4, 1.0, x, 2, 1 );
 // returns 6.25
 ```
 
@@ -183,6 +174,7 @@ var v = varianceyc.ndarray( N, 1, x, 2, 1 );
 -   If `N <= 0`, both functions return `NaN`.
 -   If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), both functions return `NaN`.
 -   Depending on the environment, the typed versions ([`dvarianceyc`][@stdlib/stats/strided/dvarianceyc], [`svarianceyc`][@stdlib/stats/strided/svarianceyc], etc.) are likely to be significantly more performant.
+-   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]).
 
 </section>
 
@@ -195,21 +187,15 @@ var v = varianceyc.ndarray( N, 1, 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/array/uniform' );
 var varianceyc = require( '@stdlib/stats/base/varianceyc' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, {
+    'dtype': 'generic'
+});
 console.log( x );
 
-var v = varianceyc( x.length, 1, x, 1 );
+var v = varianceyc( x.length, 1.0, x, 1 );
 console.log( v );
 ```
 
@@ -256,6 +242,8 @@ 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
+
 [@stdlib/stats/strided/svarianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/svarianceyc
 
 [@youngs:1971a]: https://doi.org/10.1080/00401706.1971.10488826
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.js
index c07e4bfca71e..4cf64da5f3d4 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.js
@@ -21,11 +21,18 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
-var varianceyc = require( './../lib/varianceyc.js' );
+var varianceyc = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
 
 
 // FUNCTIONS //
@@ -38,13 +45,7 @@ var varianceyc = require( './../lib/varianceyc.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		x.push( ( randu()*20.0 ) - 10.0 );
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -53,7 +54,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			v = varianceyc( x.length, 1, x, 1 );
+			v = varianceyc( x.length, 1.0, x, 1 );
 			if ( isnan( v ) ) {
 				b.fail( 'should not return NaN' );
 			}
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.ndarray.js
index 3f404dbf88e5..c760ff42df7f 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/benchmark/benchmark.ndarray.js
@@ -21,13 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
 var varianceyc = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var varianceyc = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		x.push( ( randu()*20.0 ) - 10.0 );
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -53,7 +54,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			v = varianceyc( x.length, 1, x, 1, 0 );
+			v = varianceyc( x.length, 1.0, x, 1, 0 );
 			if ( isnan( v ) ) {
 				b.fail( 'should not return NaN' );
 			}
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/varianceyc/docs/repl.txt
index 6b92bcf4f75c..2511d4ec7df5 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/docs/repl.txt
@@ -1,10 +1,10 @@
 
-{{alias}}( N, correction, x, stride )
+{{alias}}( N, correction, x, strideX )
     Computes the variance of a strided array using a one-pass algorithm proposed
     by Youngs and Cramer.
 
-    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.
@@ -31,8 +31,8 @@
     x: Array<number>|TypedArray
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length for `x`.
 
     Returns
     -------
@@ -43,30 +43,27 @@
     --------
     // Standard Usage:
     > var x = [ 1.0, -2.0, 2.0 ];
-    > {{alias}}( x.length, 1, x, 1 )
+    > {{alias}}( x.length, 1.0, x, 1 )
     ~4.3333
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, 1, x, stride )
+    > {{alias}}( 3, 1.0, x, 2 )
     ~4.3333
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     > 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, 1, x1, stride )
+    > {{alias}}( 3, 1.0, x1, 2 )
     ~4.3333
 
-{{alias}}.ndarray( N, correction, x, stride, offset )
+
+{{alias}}.ndarray( N, correction, x, strideX, offsetX )
     Computes the variance of a strided array using a one-pass algorithm proposed
     by Youngs and Cramer and alternative indexing semantics.
 
     While typed array views mandate a view offset based on the underlying
-    buffer, the `offset` parameter supports indexing semantics based on a
+    buffer, the offset parameter supports indexing semantics based on a
     starting index.
 
     Parameters
@@ -89,11 +86,11 @@
     x: Array<number>|TypedArray
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length for `x`.
 
-    offset: integer
-        Starting index.
+    offsetX: integer
+        Starting index for `x`.
 
     Returns
     -------
@@ -104,13 +101,12 @@
     --------
     // Standard Usage:
     > var x = [ 1.0, -2.0, 2.0 ];
-    > {{alias}}.ndarray( x.length, 1, x, 1, 0 )
+    > {{alias}}.ndarray( x.length, 1.0, x, 1, 0 )
     ~4.3333
 
     // Using offset parameter:
     > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, 1, x, 2, 1 )
+    > {{alias}}.ndarray( 3, 1.0, x, 2, 1 )
     ~4.3333
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/index.d.ts
index 51da248e2f8d..de3b1949ee4b 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/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 `varianceyc`.
@@ -32,16 +37,16 @@ interface Routine {
 	* @param N - number of indexed elements
 	* @param correction - degrees of freedom adjustment
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length for `x`
 	* @returns variance
 	*
 	* @example
 	* var x = [ 1.0, -2.0, 2.0 ];
 	*
-	* var v = varianceyc( x.length, 1, x, 1 );
+	* var v = varianceyc( x.length, 1.0, x, 1 );
 	* // returns ~4.3333
 	*/
-	( N: number, correction: number, x: NumericArray, stride: number ): number;
+	( N: number, correction: number, x: InputArray, strideX: number ): number;
 
 	/**
 	* Computes the variance of a strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics.
@@ -49,17 +54,17 @@ interface Routine {
 	* @param N - number of indexed elements
 	* @param correction - degrees of freedom adjustment
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length for `x`
+	* @param offsetX - starting index for `x`
 	* @returns variance
 	*
 	* @example
 	* var x = [ 1.0, -2.0, 2.0 ];
 	*
-	* var v = varianceyc.ndarray( x.length, 1, x, 1, 0 );
+	* var v = varianceyc.ndarray( x.length, 1.0, x, 1, 0 );
 	* // returns ~4.3333
 	*/
-	ndarray( N: number, correction: number, x: NumericArray, stride: number, offset: number ): number;
+	ndarray( N: number, correction: number, x: InputArray, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -68,19 +73,19 @@ interface Routine {
 * @param N - number of indexed elements
 * @param correction - degrees of freedom adjustment
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length for `x`
 * @returns variance
 *
 * @example
 * var x = [ 1.0, -2.0, 2.0 ];
 *
-* var v = varianceyc( x.length, 1, x, 1 );
+* var v = varianceyc( x.length, 1.0, x, 1 );
 * // returns ~4.3333
 *
 * @example
 * var x = [ 1.0, -2.0, 2.0 ];
 *
-* var v = varianceyc.ndarray( x.length, 1, x, 1, 0 );
+* var v = varianceyc.ndarray( x.length, 1.0, x, 1, 0 );
 * // returns ~4.3333
 */
 declare var varianceyc: Routine;
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/test.ts
index e93995ba93eb..cae7d268af9d 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/docs/types/test.ts
@@ -16,6 +16,7 @@
 * limitations under the License.
 */
 
+import AccessorArray = require( '@stdlib/array/base/accessor' );
 import varianceyc = require( './index' );
 
 
@@ -25,21 +26,22 @@ import varianceyc = require( './index' );
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc( x.length, 1, x, 1 ); // $ExpectType number
+	varianceyc( x.length, 1.0, x, 1 ); // $ExpectType number
+	varianceyc( x.length, 1.0, new AccessorArray( x ), 1 ); // $ExpectType number
 }
 
 // The compiler throws an error if the function is provided a first argument which is not a number...
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc( '10', 1, x, 1 ); // $ExpectError
-	varianceyc( true, 1, x, 1 ); // $ExpectError
-	varianceyc( false, 1, x, 1 ); // $ExpectError
-	varianceyc( null, 1, x, 1 ); // $ExpectError
-	varianceyc( undefined, 1, x, 1 ); // $ExpectError
-	varianceyc( [], 1, x, 1 ); // $ExpectError
-	varianceyc( {}, 1, x, 1 ); // $ExpectError
-	varianceyc( ( x: number ): number => x, 1, x, 1 ); // $ExpectError
+	varianceyc( '10', 1.0, x, 1 ); // $ExpectError
+	varianceyc( true, 1.0, x, 1 ); // $ExpectError
+	varianceyc( false, 1.0, x, 1 ); // $ExpectError
+	varianceyc( null, 1.0, x, 1 ); // $ExpectError
+	varianceyc( undefined, 1.0, x, 1 ); // $ExpectError
+	varianceyc( [], 1.0, x, 1 ); // $ExpectError
+	varianceyc( {}, 1.0, x, 1 ); // $ExpectError
+	varianceyc( ( x: number ): number => x, 1.0, x, 1 ); // $ExpectError
 }
 
 // The compiler throws an error if the function is provided a second argument which is not a number...
@@ -60,29 +62,29 @@ import varianceyc = require( './index' );
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc( x.length, 1, 10, 1 ); // $ExpectError
-	varianceyc( x.length, 1, '10', 1 ); // $ExpectError
-	varianceyc( x.length, 1, true, 1 ); // $ExpectError
-	varianceyc( x.length, 1, false, 1 ); // $ExpectError
-	varianceyc( x.length, 1, null, 1 ); // $ExpectError
-	varianceyc( x.length, 1, undefined, 1 ); // $ExpectError
-	varianceyc( x.length, 1, [ '1' ], 1 ); // $ExpectError
-	varianceyc( x.length, 1, {}, 1 ); // $ExpectError
-	varianceyc( x.length, 1, ( x: number ): number => x, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, 10, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, '10', 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, true, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, false, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, null, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, undefined, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, [ '1' ], 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, {}, 1 ); // $ExpectError
+	varianceyc( x.length, 1.0, ( x: number ): number => x, 1 ); // $ExpectError
 }
 
 // The compiler throws an error if the function is provided a fourth argument which is not a number...
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc( x.length, 1, x, '10' ); // $ExpectError
-	varianceyc( x.length, 1, x, true ); // $ExpectError
-	varianceyc( x.length, 1, x, false ); // $ExpectError
-	varianceyc( x.length, 1, x, null ); // $ExpectError
-	varianceyc( x.length, 1, x, undefined ); // $ExpectError
-	varianceyc( x.length, 1, x, [] ); // $ExpectError
-	varianceyc( x.length, 1, x, {} ); // $ExpectError
-	varianceyc( x.length, 1, x, ( x: number ): number => x ); // $ExpectError
+	varianceyc( x.length, 1.0, x, '10' ); // $ExpectError
+	varianceyc( x.length, 1.0, x, true ); // $ExpectError
+	varianceyc( x.length, 1.0, x, false ); // $ExpectError
+	varianceyc( x.length, 1.0, x, null ); // $ExpectError
+	varianceyc( x.length, 1.0, x, undefined ); // $ExpectError
+	varianceyc( x.length, 1.0, x, [] ); // $ExpectError
+	varianceyc( x.length, 1.0, x, {} ); // $ExpectError
+	varianceyc( x.length, 1.0, x, ( x: number ): number => x ); // $ExpectError
 }
 
 // The compiler throws an error if the function is provided an unsupported number of arguments...
@@ -91,9 +93,9 @@ import varianceyc = require( './index' );
 
 	varianceyc(); // $ExpectError
 	varianceyc( x.length ); // $ExpectError
-	varianceyc( x.length, 1 ); // $ExpectError
-	varianceyc( x.length, 1, x ); // $ExpectError
-	varianceyc( x.length, 1, x, 1, 10 ); // $ExpectError
+	varianceyc( x.length, 1.0 ); // $ExpectError
+	varianceyc( x.length, 1.0, x ); // $ExpectError
+	varianceyc( x.length, 1.0, x, 1, 10 ); // $ExpectError
 }
 
 // Attached to main export is an `ndarray` method which returns a number...
@@ -101,20 +103,21 @@ import varianceyc = require( './index' );
 	const x = new Float64Array( 10 );
 
 	varianceyc.ndarray( x.length, 1, x, 1, 0 ); // $ExpectType number
+	varianceyc.ndarray( x.length, 1, 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...
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc.ndarray( '10', 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( true, 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( false, 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( null, 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( undefined, 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( [], 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( {}, 1, x, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( ( x: number ): number => x, 1, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( '10', 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( true, 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( false, 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( null, 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( undefined, 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( [], 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( {}, 1.0, x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( ( x: number ): number => x, 1.0, x, 1, 0 ); // $ExpectError
 }
 
 // The compiler throws an error if the `ndarray` method is provided a second argument which is not a number...
@@ -135,43 +138,43 @@ import varianceyc = require( './index' );
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc.ndarray( x.length, 1, 10, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, '10', 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, true, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, false, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, null, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, undefined, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, [ '1' ], 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, {}, 1, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, ( x: number ): number => x, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, 10, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, '10', 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, true, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, false, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, null, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, undefined, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, [ '1' ], 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, {}, 1, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, ( x: number ): number => x, 1, 0 ); // $ExpectError
 }
 
 // The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number...
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc.ndarray( x.length, 1, x, '10', 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, true, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, false, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, null, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, undefined, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, [], 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, {}, 0 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, ( x: number ): number => x, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, '10', 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, true, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, false, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, null, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, undefined, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, [], 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, {}, 0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, ( x: number ): number => x, 0 ); // $ExpectError
 }
 
 // The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number...
 {
 	const x = new Float64Array( 10 );
 
-	varianceyc.ndarray( x.length, 1, x, 1, '10' ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, true ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, false ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, null ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, undefined ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, [] ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, {} ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, ( x: number ): number => x ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, '10' ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, true ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, false ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, null ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, undefined ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, [] ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, {} ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, ( x: number ): number => x ); // $ExpectError
 }
 
 // The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments...
@@ -180,8 +183,8 @@ import varianceyc = require( './index' );
 
 	varianceyc.ndarray(); // $ExpectError
 	varianceyc.ndarray( x.length ); // $ExpectError
-	varianceyc.ndarray( x.length, 1 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1 ); // $ExpectError
-	varianceyc.ndarray( x.length, 1, x, 1, 0, 10 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1 ); // $ExpectError
+	varianceyc.ndarray( x.length, 1.0, x, 1, 0, 10 ); // $ExpectError
 }
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/varianceyc/examples/index.js
index 965b058878dd..d659f7f2aa7f 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/examples/index.js
@@ -18,19 +18,13 @@
 
 '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/array/uniform' );
 var varianceyc = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, {
+	'dtype': 'generic'
+});
 console.log( x );
 
-var v = varianceyc( x.length, 1, x, 1 );
+var v = varianceyc( x.length, 1.0, x, 1 );
 console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/varianceyc.js b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/accessors.js
similarity index 62%
rename from lib/node_modules/@stdlib/stats/base/varianceyc/lib/varianceyc.js
rename to lib/node_modules/@stdlib/stats/base/varianceyc/lib/accessors.js
index 6d76e638e816..0406525482d6 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/varianceyc.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/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.
@@ -31,19 +31,28 @@
 *
 * -   Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826).
 *
+* @private
 * @param {PositiveInteger} N - number of indexed elements
 * @param {number} correction - degrees of freedom adjustment
-* @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} variance
 *
 * @example
-* var x = [ 1.0, -2.0, 2.0 ];
+* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+* var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
 *
-* var v = varianceyc( x.length, 1, x, 1 );
-* // returns ~4.3333
+* var x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+*
+* var v = varianceyc( x.length, 1.0, arraylike2object( x ), 1, 0 );
+* // returns 10.7
 */
-function varianceyc( N, correction, x, stride ) {
+function varianceyc( N, correction, x, strideX, offsetX ) {
+	var xbuf;
+	var xget;
 	var sum;
 	var ix;
 	var S;
@@ -53,26 +62,22 @@ function varianceyc( N, correction, x, stride ) {
 	var i;
 
 	n = N - correction;
-	if ( N <= 0 || n <= 0.0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return 0.0;
-	}
-	if ( stride < 0 ) {
-		ix = (1-N) * stride;
-	} else {
-		ix = 0;
-	}
-	sum = x[ ix ];
-	ix += stride;
+
+	// Cache a reference to array data:
+	xbuf = x.data;
+
+	// Cache a reference to an element accessor:
+	xget = x.accessors[ 0 ];
+
+	sum = xget( xbuf, offsetX );
+	ix = offsetX + strideX;
 	S = 0.0;
 	for ( i = 2; i <= N; i++ ) {
-		v = x[ ix ];
+		v = xget( xbuf, ix );
 		sum += v;
 		d = (i*v) - sum;
 		S += (1.0/(i*(i-1))) * d * d;
-		ix += stride;
+		ix += strideX;
 	}
 	return S / n;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/index.js
index e90497e57e78..51c01687fbb2 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/index.js
@@ -27,25 +27,29 @@
 * var varianceyc = require( '@stdlib/stats/base/varianceyc' );
 *
 * var x = [ 1.0, -2.0, 2.0 ];
-* var N = x.length;
 *
-* var v = varianceyc( N, 1, x, 1 );
+* var v = varianceyc( 3, 1.0, x, 1 );
 * // returns ~4.3333
 *
 * @example
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var varianceyc = require( '@stdlib/stats/base/varianceyc' );
 *
 * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
-* var N = floor( x.length / 2 );
 *
-* var v = varianceyc.ndarray( N, 1, x, 2, 1 );
+* var v = varianceyc.ndarray( 4, 1.0, x, 2, 1 );
 * // returns 6.25
 */
 
 // 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/varianceyc/lib/main.js b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/main.js
index 5a6b2f4f75cf..4dfe7440899e 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/main.js
@@ -20,14 +20,38 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
-var varianceyc = require( './varianceyc.js' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
 var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
 
-setReadOnly( varianceyc, 'ndarray', ndarray );
+/**
+* Computes the variance of a strided array using a one-pass algorithm proposed by Youngs and Cramer.
+*
+* ## Method
+*
+* -   This implementation uses a one-pass algorithm, as proposed by Youngs and Cramer (1971).
+*
+* ## References
+*
+* -   Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826).
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {NumericArray} x - input array
+* @param {integer} strideX - stride length
+* @returns {number} variance
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = varianceyc( x.length, 1.0, x, 1 );
+* // returns ~4.3333
+*/
+function varianceyc( N, correction, x, strideX ) {
+	return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) );
+}
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/ndarray.js
index da23fbd21f16..11c3f0cfa0e5 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/lib/ndarray.js
@@ -18,6 +18,12 @@
 
 'use strict';
 
+// MODULES //
+
+var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+var accessors = require( './accessors.js' );
+
+
 // MAIN //
 
 /**
@@ -34,20 +40,17 @@
 * @param {PositiveInteger} N - number of indexed elements
 * @param {number} correction - degrees of freedom adjustment
 * @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} variance
 *
 * @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 ];
-* var N = floor( x.length / 2 );
 *
-* var v = varianceyc( N, 1, x, 2, 1 );
+* var v = varianceyc( 4, 1.0, x, 2, 1 );
 * // returns 6.25
 */
-function varianceyc( N, correction, x, stride, offset ) {
+function varianceyc( N, correction, x, strideX, offsetX ) {
 	var sum;
 	var ix;
 	var S;
@@ -55,23 +58,30 @@ function varianceyc( N, correction, x, stride, offset ) {
 	var d;
 	var n;
 	var i;
+	var o;
 
 	n = N - correction;
 	if ( N <= 0 || n <= 0.0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return 0.0;
 	}
-	sum = x[ offset ];
-	ix = offset + stride;
+
+	o = arraylike2object( x );
+	if ( o.accessorProtocol ) {
+		return accessors( N, correction, o, strideX, offsetX );
+	}
+
+	sum = x[ offsetX ];
+	ix = offsetX + strideX;
 	S = 0.0;
 	for ( i = 2; i <= N; i++ ) {
 		v = x[ ix ];
 		sum += v;
 		d = (i*v) - sum;
 		S += (1.0/(i*(i-1))) * d * d;
-		ix += stride;
+		ix += strideX;
 	}
 	return S / n;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.main.js b/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.main.js
new file mode 100644
index 000000000000..f3335f77fef8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.main.js
@@ -0,0 +1,371 @@
+/**
+* @license Apache-2.0
+*
+* 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.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var varianceyc = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof varianceyc, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 4', function test( t ) {
+	t.strictEqual( varianceyc.length, 4, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the population variance of a strided array', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+	v = varianceyc( x.length, 0.0, x, 1 );
+	t.strictEqual( v, 53.5/x.length, 'returns expected value' );
+
+	x = [ -4.0, -4.0 ];
+	v = varianceyc( x.length, 0.0, x, 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ NaN, 4.0 ];
+	v = varianceyc( x.length, 0.0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function calculates the population variance of a strided array (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+	v = varianceyc( x.length, 0.0, toAccessorArray( x ), 1 );
+	t.strictEqual( v, 53.5/x.length, 'returns expected value' );
+
+	x = [ -4.0, -4.0 ];
+	v = varianceyc( x.length, 0.0, toAccessorArray( x ), 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ NaN, 4.0 ];
+	v = varianceyc( x.length, 0.0, toAccessorArray( x ), 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function calculates the sample variance of a strided array', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+	v = varianceyc( x.length, 1.0, x, 1 );
+	t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
+
+	x = [ -4.0, -4.0 ];
+	v = varianceyc( x.length, 1.0, x, 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ NaN, 4.0 ];
+	v = varianceyc( x.length, 1.0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function calculates the sample variance of a strided array (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 1 );
+	t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
+
+	x = [ -4.0, -4.0 ];
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ NaN, 4.0 ];
+	v = varianceyc( x.length, 1.0, 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;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = varianceyc( 0, 1.0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = varianceyc( -1, 1.0, 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 (accessor)`', function test( t ) {
+	var x;
+	var v;
+
+	x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = varianceyc( 0, 1.0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = varianceyc( -1, 1.0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = toAccessorArray( [ 10.0 ] );
+	v = varianceyc( 0, 0.0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0`', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = varianceyc( 1, 0.0, x, 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = varianceyc( 1, 0.0, x, 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = toAccessorArray( [ 5.0 ] );
+	v = varianceyc( 1, 0.0, x, 1 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = varianceyc( x.length, x.length, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = varianceyc( x.length, x.length+1, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN` (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = varianceyc( x.length, x.length, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected' );
+
+	v = varianceyc( x.length, x.length+1, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected' );
+
+	x = toAccessorArray( [ 7.0, 8.0, 9.0 ] );
+	v = varianceyc( x.length, x.length, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports a `stride` parameter', 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
+	];
+
+	v = varianceyc( 4, 1.0, x, 2 );
+
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a `stride` parameter (accessor)', 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
+	];
+
+	v = varianceyc( 4, 1.0, toAccessorArray( x ), 2 );
+
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	];
+
+	v = varianceyc( 4, 1.0, x, -2 );
+
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	];
+
+	v = varianceyc( 4, 1.0, toAccessorArray( x ), -2 );
+
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = varianceyc( x.length, 1.0, x, 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports view offsets', 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
+	]);
+
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+	v = varianceyc( 4, 1.0, x1, 2 );
+	t.strictEqual( v, 6.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports view offsets (accessor)', 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
+	]);
+
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+	v = varianceyc( 4, 1.0, toAccessorArray( x1 ), 2 );
+	t.strictEqual( v, 6.25, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.ndarray.js
index d479be840e45..65440b321483 100644
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.ndarray.js
@@ -21,7 +21,7 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var varianceyc = require( './../lib/ndarray.js' );
 
@@ -44,15 +44,34 @@ tape( 'the function calculates the population variance of a strided array', func
 	var v;
 
 	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
-	v = varianceyc( x.length, 0, x, 1, 0 );
+	v = varianceyc( x.length, 0.0, x, 1, 0 );
 	t.strictEqual( v, 53.5/x.length, 'returns expected value' );
 
 	x = [ -4.0, -4.0 ];
-	v = varianceyc( x.length, 0, x, 1, 0 );
+	v = varianceyc( x.length, 0.0, x, 1, 0 );
 	t.strictEqual( v, 0.0, 'returns expected value' );
 
 	x = [ NaN, 4.0 ];
-	v = varianceyc( x.length, 0, x, 1, 0 );
+	v = varianceyc( x.length, 0.0, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function calculates the population variance of a strided array (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+	v = varianceyc( x.length, 0.0, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( v, 53.5/x.length, 'returns expected value' );
+
+	x = [ -4.0, -4.0 ];
+	v = varianceyc( x.length, 0.0, toAccessorArray( x ), 1, 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ NaN, 4.0 ];
+	v = varianceyc( x.length, 0.0, toAccessorArray( x ), 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
@@ -63,15 +82,34 @@ tape( 'the function calculates the sample variance of a strided array', function
 	var v;
 
 	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
-	v = varianceyc( x.length, 1, x, 1, 0 );
+	v = varianceyc( x.length, 1.0, x, 1, 0 );
+	t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
+
+	x = [ -4.0, -4.0 ];
+	v = varianceyc( x.length, 1.0, x, 1, 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ NaN, 4.0 ];
+	v = varianceyc( x.length, 1.0, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function calculates the sample variance of a strided array (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 1, 0 );
 	t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
 
 	x = [ -4.0, -4.0 ];
-	v = varianceyc( x.length, 1, x, 1, 0 );
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 1, 0 );
 	t.strictEqual( v, 0.0, 'returns expected value' );
 
 	x = [ NaN, 4.0 ];
-	v = varianceyc( x.length, 1, x, 1, 0 );
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
@@ -83,10 +121,29 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 
 	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
 
-	v = varianceyc( 0, 1, x, 1, 0 );
+	v = varianceyc( 0, 1.0, x, 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
-	v = varianceyc( -1, 1, x, 1, 0 );
+	v = varianceyc( -1, 1.0, 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` (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = varianceyc( 0, 1.0, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = varianceyc( -1, 1.0, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = toAccessorArray( [ 10.0 ] );
+	v = varianceyc( 0, 0.0, x, 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
@@ -98,7 +155,23 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a populat
 
 	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
 
-	v = varianceyc( 1, 0, x, 1, 0 );
+	v = varianceyc( 1, 0.0, x, 1, 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = varianceyc( 1, 0.0, x, 1, 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = toAccessorArray( [ 5.0 ] );
+	v = varianceyc( 1, 0.0, x, 1, 0 );
 	t.strictEqual( v, 0.0, 'returns expected value' );
 
 	t.end();
@@ -119,8 +192,26 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
 	t.end();
 });
 
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN (accessor)`', function test( t ) {
+	var x;
+	var v;
+
+	x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = varianceyc( x.length, x.length, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = varianceyc( x.length, x.length+1, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = toAccessorArray( [ 7.0, 8.0, 9.0 ] );
+	v = varianceyc( x.length, x.length, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -135,15 +226,34 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	];
 
-	N = floor( x.length / 2 );
-	v = varianceyc( N, 1, x, 2, 0 );
+	v = varianceyc( 4, 1.0, x, 2, 0 );
+
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a `stride` parameter (accessor)', 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
+	];
+
+	v = varianceyc( 4, 1.0, toAccessorArray( x ), 2, 0 );
 
 	t.strictEqual( v, 6.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -158,8 +268,28 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	];
 
-	N = floor( x.length / 2 );
-	v = varianceyc( N, 1, x, -2, 6 );
+	v = varianceyc( 4, 1.0, x, -2, 6 );
+
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	];
+
+	v = varianceyc( 4, 1.0, toAccessorArray( x ), -2, 6 );
 
 	t.strictEqual( v, 6.25, 'returns expected value' );
 	t.end();
@@ -171,14 +301,25 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`',
 
 	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
 
-	v = varianceyc( x.length, 1, x, 0, 0 );
+	v = varianceyc( x.length, 1.0, x, 0, 0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` (accessor)', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+	v = varianceyc( x.length, 1.0, toAccessorArray( x ), 0, 0 );
 	t.strictEqual( v, 0.0, 'returns expected value' );
 
 	t.end();
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -192,10 +333,27 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	];
-	N = floor( x.length / 2 );
 
-	v = varianceyc( N, 1, x, 2, 1 );
+	v = varianceyc( 4, 1.0, x, 2, 1 );
 	t.strictEqual( v, 6.25, 'returns expected value' );
 
 	t.end();
 });
+
+tape( 'the function supports an `offset` parameter (accessor)', 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
+	];
+	v = varianceyc( 4, 1.0, toAccessorArray( x ), 2, 1 );
+	t.strictEqual( v, 6.25, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.varianceyc.js b/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.varianceyc.js
deleted file mode 100644
index 4ff7dd76fcf8..000000000000
--- a/lib/node_modules/@stdlib/stats/base/varianceyc/test/test.varianceyc.js
+++ /dev/null
@@ -1,206 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 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.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-'use strict';
-
-// MODULES //
-
-var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var Float64Array = require( '@stdlib/array/float64' );
-var varianceyc = require( './../lib/varianceyc.js' );
-
-
-// TESTS //
-
-tape( 'main export is a function', function test( t ) {
-	t.ok( true, __filename );
-	t.strictEqual( typeof varianceyc, 'function', 'main export is a function' );
-	t.end();
-});
-
-tape( 'the function has an arity of 4', function test( t ) {
-	t.strictEqual( varianceyc.length, 4, 'has expected arity' );
-	t.end();
-});
-
-tape( 'the function calculates the population variance of a strided array', function test( t ) {
-	var x;
-	var v;
-
-	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
-	v = varianceyc( x.length, 0, x, 1 );
-	t.strictEqual( v, 53.5/x.length, 'returns expected value' );
-
-	x = [ -4.0, -4.0 ];
-	v = varianceyc( x.length, 0, x, 1 );
-	t.strictEqual( v, 0.0, 'returns expected value' );
-
-	x = [ NaN, 4.0 ];
-	v = varianceyc( x.length, 0, x, 1 );
-	t.strictEqual( isnan( v ), true, 'returns expected value' );
-
-	t.end();
-});
-
-tape( 'the function calculates the sample variance of a strided array', function test( t ) {
-	var x;
-	var v;
-
-	x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
-	v = varianceyc( x.length, 1, x, 1 );
-	t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
-
-	x = [ -4.0, -4.0 ];
-	v = varianceyc( x.length, 1, x, 1 );
-	t.strictEqual( v, 0.0, 'returns expected value' );
-
-	x = [ NaN, 4.0 ];
-	v = varianceyc( x.length, 1, 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;
-
-	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
-
-	v = varianceyc( 0, 1, x, 1 );
-	t.strictEqual( isnan( v ), true, 'returns expected value' );
-
-	v = varianceyc( -1, 1, x, 1 );
-	t.strictEqual( isnan( v ), true, 'returns expected value' );
-
-	t.end();
-});
-
-tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0`', function test( t ) {
-	var x;
-	var v;
-
-	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
-
-	v = varianceyc( 1, 0, x, 1 );
-	t.strictEqual( v, 0.0, 'returns expected value' );
-
-	t.end();
-});
-
-tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) {
-	var x;
-	var v;
-
-	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
-
-	v = varianceyc( x.length, x.length, x, 1 );
-	t.strictEqual( isnan( v ), true, 'returns expected value' );
-
-	v = varianceyc( x.length, x.length+1, x, 1 );
-	t.strictEqual( isnan( v ), true, 'returns expected value' );
-
-	t.end();
-});
-
-tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
-	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
-	];
-
-	N = floor( x.length / 2 );
-	v = varianceyc( N, 1, x, 2 );
-
-	t.strictEqual( v, 6.25, 'returns expected value' );
-	t.end();
-});
-
-tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
-	var x;
-	var v;
-
-	x = [
-		1.0,  // 3
-		2.0,
-		2.0,  // 2
-		-7.0,
-		-2.0, // 1
-		3.0,
-		4.0,  // 0
-		2.0
-	];
-
-	N = floor( x.length / 2 );
-	v = varianceyc( N, 1, x, -2 );
-
-	t.strictEqual( v, 6.25, 'returns expected value' );
-	t.end();
-});
-
-tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', function test( t ) {
-	var x;
-	var v;
-
-	x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
-
-	v = varianceyc( x.length, 1, x, 0 );
-	t.strictEqual( v, 0.0, '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([
-		2.0,
-		1.0,  // 0
-		2.0,
-		-2.0, // 1
-		-2.0,
-		2.0,  // 2
-		3.0,
-		4.0,  // 3
-		6.0
-	]);
-
-	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
-
-	v = varianceyc( N, 1, x1, 2 );
-	t.strictEqual( v, 6.25, 'returns expected value' );
-
-	t.end();
-});