diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/README.md b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/README.md
index 60abf2661988..4110f8813024 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/README.md
@@ -122,21 +122,19 @@ 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 [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **out**: output [`Float64Array`][@stdlib/array/float64] for storing results.
--   **strideOut**: index increment for `out`.
+-   **strideOut**: stride length for `out`.
 
-The `N` and `stride` parameters determine which elements 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 arrays are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
 var out = new Float64Array( 2 );
-var N = floor( x.length / 2 );
 
-var v = dmeanvarpn( N, 1, x, 2, out, 1 );
+var v = dmeanvarpn( 4, 1, x, 2, out, 1 );
 // returns <Float64Array>[ 1.25, 6.25 ]
 ```
 
@@ -146,7 +144,6 @@ 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
@@ -154,9 +151,7 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var out0 = new Float64Array( 4 );
 var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element
 
-var N = floor( x0.length / 2 );
-
-var v = dmeanvarpn( N, 1, x1, 2, out1, 1 );
+var v = dmeanvarpn( 4, 1, x1, 2, out1, 1 );
 // returns <Float64Array>[ 1.25, 6.25 ]
 ```
 
@@ -179,17 +174,15 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetOut**: starting index for `out`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameters support indexing semantics based on a starting index. For example, to calculate the [mean][arithmetic-mean] and [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 parameters support indexing semantics based on a starting index. For example, to calculate the [mean][arithmetic-mean] and [variance][variance] for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var out = new Float64Array( 4 );
-var N = floor( x.length / 2 );
 
-var v = dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 2, 1 );
+var v = dmeanvarpn.ndarray( 4, 1, x, 2, 1, out, 2, 1 );
 // returns <Float64Array>[ 0.0, 1.25, 0.0, 6.25 ]
 ```
 
@@ -215,22 +208,16 @@ var v = dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dmeanvarpn = require( '@stdlib/stats/base/dmeanvarpn' );
 
-var out;
-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 = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});
 console.log( x );
 
-out = new Float64Array( 2 );
+var out = new Float64Array( 2 );
 dmeanvarpn( x.length, 1, x, 1, out, 1 );
 console.log( out );
 ```
@@ -239,6 +226,135 @@ console.log( out );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmeanvarpn.h"
+```
+
+#### stdlib_strided_dmeanvarpn( N, correction, \*X, strideX, \*Out, strideOut )
+
+Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using a two-pass algorithm.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+double out[] = { 0.0, 0.0 }
+
+stdlib_strided_dmeanvarpn( 3, 1.0, x, 1, out, 1 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **correction**: `[in] double` 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**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Out**: `[out] double*` output array.
+-   **strideOut**: `[in] CBLAS_INT` stride length for `Out`.
+
+```c
+double stdlib_strided_dmeanvarpn( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut );
+```
+
+#### stdlib_strided_dmeanvarpn( N, correction, \*X, strideX, offsetX, \*Out, strideOut, offsetOut )
+
+Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using a two-pass algorithm and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+double out[] = { 0.0, 0.0 }
+
+stdlib_strided_dmeanvarpn_ndarray( 3, 1.0, x, 1, 0, out, 1, 0 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **correction**: `[in] double` 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**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Out**: `[out] double*` output array.
+-   **strideOut**: `[in] CBLAS_INT` stride length for `Out`.
+-   **offsetOut**: `[in] CBLAS_INT` starting index for `Out`.
+
+```c
+double stdlib_strided_dmeanvarpn_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmeanvarpn.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+
+    // Create an output array:
+    double out[] = { 0.0, 0.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideOut = 1;
+
+    // Compute the mean and variance:
+    stdlib_strided_dmeanvarpn( N, 1.0, x, strideX, out, strideOut );
+
+    // Print the result:
+    printf( "sample mean: %lf\n", out[ 0 ] );
+    printf( "sample variance: %lf\n", out[ 1 ] );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 * * *
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.js
index 592209cce648..88b13051e76d 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.js
@@ -21,7 +21,7 @@
 // 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 Float64Array = require( '@stdlib/array/float64' );
@@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name;
 var dmeanvarpn = require( './../lib/dmeanvarpn.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dmeanvarpn = require( './../lib/dmeanvarpn.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var out;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	out = new Float64Array( 2 );
+	var out = new Float64Array( 2 );
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.native.js
index f13dda43bad8..5ea0f9d969dd 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.native.js
@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 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 Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dmeanvarpn = tryRequire( resolve( __dirname, './../lib/dmeanvarpn.native.js'
 var opts = {
 	'skip': ( dmeanvarpn instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var out;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	out = new Float64Array( 2 );
+	var out = new Float64Array( 2 );
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.js
index fee5a2ea4af9..45fde9c54b5b 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.js
@@ -21,7 +21,7 @@
 // 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 Float64Array = require( '@stdlib/array/float64' );
@@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name;
 var dmeanvarpn = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dmeanvarpn = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var out;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	out = new Float64Array( 2 );
+	var out = new Float64Array( 2 );
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.native.js
index 4e99b0dce5f2..adb5acd0a7e3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/benchmark.ndarray.native.js
@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 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 Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dmeanvarpn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' )
 var opts = {
 	'skip': ( dmeanvarpn instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var out;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
-	out = new Float64Array( 2 );
+	var out = new Float64Array( 2 );
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/c/benchmark.length.c
index 3db79d89d345..e14861d588ab 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double out[ 2 ];
 	double x[ len ];
@@ -109,6 +109,7 @@ static double benchmark( int iterations, int len ) {
 
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		stdlib_strided_dmeanvarpn( len, 1, x, 1, out, 1 );
 		if ( out[ i%2 ] != out[ i%2 ] ) {
 			printf( "should not return NaN\n" );
@@ -122,6 +123,42 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double out[ 2 ];
+	double x[ len ];
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+	}
+	out[ 0 ] = 0.0;
+	out[ 1 ] = 0.0;
+
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		stdlib_strided_dmeanvarpn_ndarray( len, 1, x, 1, 0, out, 1, 0 );
+		if ( out[ i%2 ] != out[ i%2 ] ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( out[ i%2 ] != out[ i%2 ] ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -144,7 +181,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/docs/repl.txt
index c02ea1914fbc..564f6f8e4c25 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the mean and variance of a double-precision floating-point strided
     array using a two-pass algorithm.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -32,13 +32,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride length for `x`.
 
     out: Float64Array
         Output array.
 
     strideOut: integer
-        Index increment for `out`.
+        Stride length for `out`.
 
     Returns
     -------
@@ -53,21 +53,20 @@
     > {{alias}}( x.length, 1, x, 1, out, 1 )
     <Float64Array>[ ~0.3333, ~4.3333 ]
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
     > out = new {{alias:@stdlib/array/float64}}( 2 );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, 1, x, 2, out, 1 )
+    > {{alias}}( 3, 1, x, 2, out, 1 )
     <Float64Array>[ ~0.3333, ~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 );
     > out = new {{alias:@stdlib/array/float64}}( 2 );
-    > {{alias}}( N, 1, x1, 2, out, 1 )
+    > {{alias}}( 3, 1, x1, 2, out, 1 )
     <Float64Array>[ ~0.3333, ~4.3333 ]
 
+
 {{alias}}.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )
     Computes the mean and variance of a double-precision floating-point strided
     array using a two-pass algorithm and alternative indexing semantics.
@@ -97,7 +96,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -106,7 +105,7 @@
         Output array.
 
     strideOut: integer
-        Index increment for `out`.
+        Stride length for `out`.
 
     offsetOut: integer
         Starting index for `out`.
@@ -126,9 +125,8 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
     > out = new {{alias:@stdlib/array/float64}}( 2 );
-    > {{alias}}.ndarray( N, 1, x, 2, 1, out, 1, 0 )
+    > {{alias}}.ndarray( 3, 1, x, 2, 1, out, 1, 0 )
     <Float64Array>[ ~0.3333, ~4.3333 ]
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/c/example.c
index c48fcbfb0b05..0dfab869ad40 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/c/example.c
@@ -17,25 +17,24 @@
 */
 
 #include "stdlib/stats/base/dmeanvarpn.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
 
 	// Create an output array:
 	double out[] = { 0.0, 0.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride lengths:
-	int64_t strideX = 2;
-	int64_t strideOut = 1;
+	const int strideX = 2;
+	const int strideOut = 1;
 
 	// Compute the mean and variance:
-	stdlib_strided_dmeanvarpn( N, 1, x, strideX, out, strideOut );
+	stdlib_strided_dmeanvarpn( N, 1.0, x, strideX, out, strideOut );
 
 	// Print the result:
 	printf( "sample mean: %lf\n", out[ 0 ] );
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/index.js
index 8b499cc3d2a6..cf78d1a6999d 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/examples/index.js
@@ -18,21 +18,15 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dmeanvarpn = require( './../lib' );
 
-var out;
-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 = discreteUniform( 10, -50, 50, {
+	'dtype': 'float64'
+});
 console.log( x );
 
-out = new Float64Array( 2 );
+var out = new Float64Array( 2 );
 dmeanvarpn( x.length, 1, x, 1, out, 1 );
 console.log( out );
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include/stdlib/stats/base/dmeanvarpn.h b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include/stdlib/stats/base/dmeanvarpn.h
index 41c114af124c..7fca7d19a3ff 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include/stdlib/stats/base/dmeanvarpn.h
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include/stdlib/stats/base/dmeanvarpn.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMEANVARPN_H
 #define STDLIB_STATS_BASE_DMEANVARPN_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.
 */
-void stdlib_strided_dmeanvarpn( const int64_t N, const double correction, const double *X, const int64_t strideX, double *Out, const int64_t strideOut );
+void API_SUFFIX(stdlib_strided_dmeanvarpn)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut );
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using a two-pass algorithm and alternative indexing semantics.
+*/
+void API_SUFFIX(stdlib_strided_dmeanvarpn_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/dmeanvarpn.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/dmeanvarpn.js
index e41ced9e23a2..35e62991b290 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/dmeanvarpn.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/dmeanvarpn.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -56,66 +56,9 @@ var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' );
 * // returns <Float64Array>[ ~0.3333, ~4.3333 ]
 */
 function dmeanvarpn( N, correction, x, strideX, out, strideOut ) {
-	var mu;
-	var ix;
-	var io;
-	var M2;
-	var M;
-	var d;
-	var c;
-	var n;
-	var i;
-
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideOut < 0 ) {
-		io = -strideOut;
-	} else {
-		io = 0;
-	}
-	if ( N <= 0 ) {
-		out[ io ] = NaN;
-		out[ io+strideOut ] = NaN;
-		return out;
-	}
-	n = N - correction;
-	if ( N === 1 || strideX === 0 ) {
-		out[ io ] = x[ ix ];
-		if ( n <= 0.0 ) {
-			out[ io+strideOut ] = NaN;
-		} else {
-			out[ io+strideOut ] = 0.0;
-		}
-		return out;
-	}
-	// Compute an estimate for the mean:
-	mu = dsumpw( N, x, strideX ) / N;
-	if ( isnan( mu ) ) {
-		out[ io ] = NaN;
-		out[ io+strideOut ] = NaN;
-		return out;
-	}
-	// Compute the sum of squared differences from the mean...
-	M2 = 0.0;
-	M = 0.0;
-	for ( i = 0; i < N; i++ ) {
-		d = x[ ix ] - mu;
-		M2 += d * d;
-		M += d;
-		ix += strideX;
-	}
-	// Compute an error term for the mean:
-	c = M / N;
-
-	out[ io ] = mu + c;
-	if ( n <= 0.0 ) {
-		out[ io+strideOut ] = NaN;
-	} else {
-		out[ io+strideOut ] = (M2/n) - (c*(M/n));
-	}
+	var ox = stride2offset( N, strideX );
+	var oo = ( strideOut >= 0 ) ? 0 : -strideOut;
+	ndarray( N, correction, x, strideX, ox, out, strideOut, oo );
 	return out;
 }
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/index.js
index adde9d89744d..1a12d2664ca7 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/index.js
@@ -35,15 +35,12 @@
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dmeanvarpn = require( '@stdlib/stats/base/dmeanvarpn' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var out = new Float64Array( 2 );
 *
-* var N = floor( x.length / 2 );
-*
-* var v = dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 );
+* var v = dmeanvarpn.ndarray( 4, 1, x, 2, 1, out, 1, 0 );
 * // returns <Float64Array>[ 1.25, 6.25 ]
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.js
index 258e78ed963d..2a9424f0aeab 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.js
@@ -50,14 +50,11 @@ var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ).ndarray;
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var out = new Float64Array( 2 );
 *
-* var N = floor( x.length / 2 );
-*
-* var v = dmeanvarpn( N, 1, x, 2, 1, out, 1, 0 );
+* var v = dmeanvarpn( 4, 1, x, 2, 1, out, 1, 0 );
 * // returns <Float64Array>[ 1.25, 6.25 ]
 */
 function dmeanvarpn( N, correction, x, strideX, offsetX, out, strideOut, offsetOut ) { // eslint-disable-line max-len
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.native.js
index 9331ba7f314e..fd662dba5c93 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dmeanvarpn.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -41,28 +40,15 @@ var addon = require( './dmeanvarpn.native.js' );
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var out = new Float64Array( 2 );
 *
-* var N = floor( x.length / 2 );
-*
-* var v = dmeanvarpn( N, 1, x, 2, 1, out, 1, 0 );
+* var v = dmeanvarpn( 4, 1, x, 2, 1, out, 1, 0 );
 * // returns <Float64Array>[ 1.25, 6.25 ]
 */
 function dmeanvarpn( N, correction, x, strideX, offsetX, out, strideOut, offsetOut ) { // eslint-disable-line max-len
-	var viewOut;
-	var viewX;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideOut < 0 ) {
-		offsetOut += strideOut;
-	}
-	viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewOut = new Float64Array( out.buffer, out.byteOffset+(out.BYTES_PER_ELEMENT*offsetOut), out.length-offsetOut ); // eslint-disable-line max-len
-	addon( N, correction, viewX, strideX, viewOut, strideOut );
+	addon.ndarray( N, correction, x, strideX, offsetX, out, strideOut, offsetOut ); // eslint-disable-line max-len
 	return out;
 }
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/manifest.json
index 24cdd6afec91..02e992690462 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task": "build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,56 +28,79 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
         "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/blas/ext/base/dsumpw",
+        "@stdlib/math/base/assert/is-nan",
         "@stdlib/napi/export",
         "@stdlib/napi/argv",
         "@stdlib/napi/argv-int64",
         "@stdlib/napi/argv-double",
-        "@stdlib/napi/argv-strided-float64array",
-        "@stdlib/blas/base/shared",
-        "@stdlib/blas/ext/base/dsumpw"
+        "@stdlib/napi/argv-strided-float64array"
       ]
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
         "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/blas/ext/base/dsumpw"
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/blas/ext/base/dsumpw",
+        "@stdlib/math/base/assert/is-nan"
       ]
     },
     {
       "task": "examples",
+      "wasm": false,
       "src": [
         "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/blas/ext/base/dsumpw",
+        "@stdlib/math/base/assert/is-nan"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
       ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/blas/ext/base/dsumpw"
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/blas/ext/base/dsumpw",
+        "@stdlib/math/base/assert/is-nan"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.c
index ee2eb574e77b..259cc9b026e0 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.c
@@ -44,4 +44,25 @@ static napi_value addon( napi_env env, napi_callback_info info ) {
 	return NULL;
 }
 
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 8 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 6 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetOut, argv, 7 );
+	STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, 2, strideOut, argv, 5 );
+	API_SUFFIX(stdlib_strided_dmeanvarpn_ndarray)( N, correction, X, strideX, offsetX, Out, strideOut, offsetOut );
+	return NULL;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/main.c
index 6f17bdfdaa53..a2cdb5f034c3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/main.c
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/main.c
@@ -18,7 +18,9 @@
 
 #include "stdlib/stats/base/dmeanvarpn.h"
 #include "stdlib/blas/ext/base/dsumpw.h"
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
+#include "stdlib/math/base/assert/is_nan.h"
 
 /**
 * Computes the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.
@@ -39,10 +41,29 @@
 * @param Out         output array
 * @param strideOut   Out stride length
 */
-void stdlib_strided_dmeanvarpn( const int64_t N, const double correction, const double *X, const int64_t strideX, double *Out, const int64_t strideOut ) {
-	int64_t ix;
-	int64_t io;
-	int64_t i;
+void API_SUFFIX(stdlib_strided_dmeanvarpn)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut ) {
+	const CBLAS_INT oo = strideOut >= 0 ? 0 : -strideOut;
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	API_SUFFIX(stdlib_strided_dmeanvarpn_ndarray)( N, correction, X, strideX, ox, Out, strideOut, oo );
+	return;
+}
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using a two-pass algorithm and alternative indexing semantics.
+*
+* @param N           number of indexed elements
+* @param correction  degrees of freedom adjustment
+* @param X           input array
+* @param strideX     X stride length
+* @param offsetX     starting index for X
+* @param Out         output array
+* @param strideOut   Out stride length
+* @param offsetOut   starting index for Out
+*/
+void API_SUFFIX(stdlib_strided_dmeanvarpn_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ) {
+	CBLAS_INT ix;
+	CBLAS_INT io;
+	CBLAS_INT i;
 	double M2;
 	double mu;
 	double dN;
@@ -51,16 +72,8 @@ void stdlib_strided_dmeanvarpn( const int64_t N, const double correction, const
 	double c;
 	double n;
 
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideOut < 0 ) {
-		io = -strideOut;
-	} else {
-		io = 0;
-	}
+	ix = offsetX;
+	io = offsetOut;
 	if ( N <= 0 ) {
 		Out[ io ] = 0.0 / 0.0; // NaN
 		Out[ io+strideOut ] = 0.0 / 0.0; // NaN
@@ -78,8 +91,8 @@ void stdlib_strided_dmeanvarpn( const int64_t N, const double correction, const
 		return;
 	}
 	// Compute an estimate for the mean:
-	mu = stdlib_strided_dsumpw( N, X, strideX ) / dN;
-	if ( mu != mu ) {
+	mu = API_SUFFIX(stdlib_strided_dsumpw_ndarray)( N, X, strideX, offsetX ) / dN;
+	if ( stdlib_base_is_nan( mu ) ) {
 		Out[ io ] = 0.0 / 0.0; // NaN
 		Out[ io+strideOut ] = 0.0 / 0.0; // NaN
 		return;
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.js
index 427919e733ba..aa5fe726634c 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.js
@@ -21,7 +21,6 @@
 // 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 dmeanvarpn = require( './../lib/dmeanvarpn.js' );
@@ -188,7 +187,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -204,8 +202,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, 2, out, 2 );
+	v = dmeanvarpn( 4, 1, x, 2, out, 2 );
 
 	expected = new Float64Array( [ 1.25, 0.0, 6.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -216,7 +213,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -232,8 +228,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, -2, out, -2 );
+	v = dmeanvarpn( 4, 1, x, -2, out, -2 );
 
 	expected = new Float64Array( [ 6.25, 0.0, 1.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -265,7 +260,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var out1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -283,9 +277,8 @@ tape( 'the function supports view offsets', function test( t ) {
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at the 3rd element
-	N = floor(x1.length / 2);
 
-	v = dmeanvarpn( N, 1, x1, 2, out1, 1 );
+	v = dmeanvarpn( 4, 1, x1, 2, out1, 1 );
 
 	expected0 = new Float64Array( [ 0.0, 0.0, 1.25, 6.25 ] );
 	expected1 = new Float64Array( [ 1.25, 6.25 ] );
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.native.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.native.js
index 196fafaef1ce..39f35eb9d21c 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.dmeanvarpn.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 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 tryRequire = require( '@stdlib/utils/try-require' );
@@ -197,7 +196,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -213,8 +211,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, 2, out, 2 );
+	v = dmeanvarpn( 4, 1, x, 2, out, 2 );
 
 	expected = new Float64Array( [ 1.25, 0.0, 6.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -225,7 +222,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -241,8 +237,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, -2, out, -2 );
+	v = dmeanvarpn( 4, 1, x, -2, out, -2 );
 
 	expected = new Float64Array( [ 6.25, 0.0, 1.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -274,7 +269,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var out1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -292,9 +286,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at the 3rd element
-	N = floor(x1.length / 2);
 
-	v = dmeanvarpn( N, 1, x1, 2, out1, 1 );
+	v = dmeanvarpn( 4, 1, x1, 2, out1, 1 );
 
 	expected0 = new Float64Array( [ 0.0, 0.0, 1.25, 6.25 ] );
 	expected1 = new Float64Array( [ 1.25, 6.25 ] );
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.js
index f1c1ee448522..5908e1c6e2cf 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // 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 dmeanvarpn = require( './../lib/ndarray.js' );
@@ -188,7 +187,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -204,8 +202,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, 2, 0, out, 2, 0 );
+	v = dmeanvarpn( 4, 1, x, 2, 0, out, 2, 0 );
 
 	expected = new Float64Array( [ 1.25, 0.0, 6.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -216,7 +213,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -232,8 +228,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, -2, 6, out, -2, 2 );
+	v = dmeanvarpn( 4, 1, x, -2, 6, out, -2, 2 );
 
 	expected = new Float64Array( [ 6.25, 0.0, 1.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -261,7 +256,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns an ar
 tape( 'the function supports `offset` parameters', function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -276,9 +270,8 @@ tape( 'the function supports `offset` parameters', function test( t ) {
 		4.0   // 3
 	]);
 	out = new Float64Array( 4 );
-	N = floor( x.length / 2 );
 
-	v = dmeanvarpn( N, 1, x, 2, 1, out, 2, 1 );
+	v = dmeanvarpn( 4, 1, x, 2, 1, out, 2, 1 );
 
 	expected = new Float64Array( [ 0.0, 1.25, 0.0, 6.25 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.native.js
index b1359bbee20e..a0d5b3211fa8 100644
--- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 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 tryRequire = require( '@stdlib/utils/try-require' );
@@ -197,7 +196,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -213,8 +211,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, 2, 0, out, 2, 0 );
+	v = dmeanvarpn( 4, 1, x, 2, 0, out, 2, 0 );
 
 	expected = new Float64Array( [ 1.25, 0.0, 6.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -225,7 +222,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -241,8 +237,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 	]);
 	out = new Float64Array( 4 );
 
-	N = floor( x.length / 2 );
-	v = dmeanvarpn( N, 1, x, -2, 6, out, -2, 2 );
+	v = dmeanvarpn( 4, 1, x, -2, 6, out, -2, 2 );
 
 	expected = new Float64Array( [ 6.25, 0.0, 1.25, 0.0 ] );
 	t.deepEqual( v, expected, 'returns expected value' );
@@ -270,7 +265,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns an ar
 tape( 'the function supports `offset` parameters', opts, function test( t ) {
 	var expected;
 	var out;
-	var N;
 	var x;
 	var v;
 
@@ -285,9 +279,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) {
 		4.0   // 3
 	]);
 	out = new Float64Array( 4 );
-	N = floor( x.length / 2 );
 
-	v = dmeanvarpn( N, 1, x, 2, 1, out, 2, 1 );
+	v = dmeanvarpn( 4, 1, x, 2, 1, out, 2, 1 );
 
 	expected = new Float64Array( [ 0.0, 1.25, 0.0, 6.25 ] );
 	t.deepEqual( v, expected, 'returns expected value' );