diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/README.md b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/README.md
new file mode 100644
index 000000000000..b19e658e6f57
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/README.md
@@ -0,0 +1,418 @@
+
+
+
+
+# dmeanvarwd
+
+> Calculate the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using Welford's algorithm.
+
+
+
+The population [variance][variance] of a finite size population of size `N` is given by
+
+
+
+```math
+\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2
+```
+
+
+
+
+
+where the population mean is given by
+
+
+
+```math
+\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i
+```
+
+
+
+
+
+Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields a **biased sample variance**. To compute an **unbiased sample variance** for a sample of size `n`,
+
+
+
+```math
+s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2
+```
+
+
+
+
+
+where the sample mean is given by
+
+
+
+```math
+\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i
+```
+
+
+
+
+
+The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var dmeanvarwd = require( '@stdlib/stats/strided/dmeanvarwd' );
+```
+
+#### dmeanvarwd( N, correction, x, strideX, out, strideOut )
+
+Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using Welford's algorithm.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+var out = new Float64Array( 2 );
+
+var v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+// returns [ ~0.3333, ~4.3333 ]
+
+var bool = ( v === out );
+// returns true
+```
+
+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**: stride length for `x`.
+- **out**: output [`Float64Array`][@stdlib/array/float64] for storing results.
+- **strideOut**: stride length for `out`.
+
+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 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 v = dmeanvarwd( 4, 1, x, 2, out, 1 );
+// returns [ 1.25, 6.25 ]
+```
+
+Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
+
+
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+var out0 = new Float64Array( 4 );
+var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element
+
+var v = dmeanvarwd( 4, 1, x1, 2, out1, 1 );
+// returns [ 1.25, 6.25 ]
+```
+
+#### dmeanvarwd.ndarray( 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 Welford's algorithm and alternative indexing semantics.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+var out = new Float64Array( 2 );
+
+var v = dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, 0 );
+// returns [ ~0.3333, ~4.3333 ]
+```
+
+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 element in `x` starting from the second element
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+var out = new Float64Array( 4 );
+
+var v = dmeanvarwd.ndarray( 4, 1, x, 2, 1, out, 2, 1 );
+// returns [ 0.0, 1.25, 0.0, 6.25 ]
+```
+
+
+
+
+
+
+
+## Notes
+
+- If `N <= 0`, both functions return a [mean][arithmetic-mean] and [variance][variance] equal to `NaN`.
+- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), both functions return a [variance][variance] equal to `NaN`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var dmeanvarwd = require( '@stdlib/stats/strided/dmeanvarwd' );
+
+var x = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float64'
+});
+console.log( x );
+
+var out = new Float64Array( 2 );
+dmeanvarwd( x.length, 1, x, 1, out, 1 );
+console.log( out );
+```
+
+
+
+
+
+
+
+* * *
+
+
+
+## C APIs
+
+
+
+
+
+
+
+
+
+
+
+### Usage
+
+```c
+#include "stdlib/stats/strided/dmeanvarwd.h"
+```
+
+#### stdlib_strided_dmeanvarwd( N, correction, \*X, strideX, \*Out, strideOut )
+
+Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using Welford's algorithm.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+double out[] = { 0.0, 0.0 }
+
+stdlib_strided_dmeanvarwd( 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_dmeanvarwd( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut );
+```
+
+#### stdlib_strided_dmeanvarwd( 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 Welford's algorithm and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+double out[] = { 0.0, 0.0 }
+
+stdlib_strided_dmeanvarwd_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_dmeanvarwd_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 );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+### Examples
+
+```c
+#include "stdlib/stats/strided/dmeanvarwd.h"
+#include
+
+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_dmeanvarwd( N, 1.0, x, strideX, out, strideOut );
+
+ // Print the result:
+ printf( "sample mean: %lf\n", out[ 0 ] );
+ printf( "sample variance: %lf\n", out[ 1 ] );
+}
+```
+
+
+
+
+
+
+
+
+
+* * *
+
+
+
+## References
+
+- Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022][@welford:1962a].
+- van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961][@vanreeken:1968a].
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[variance]: https://en.wikipedia.org/wiki/Variance
+
+[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
+
+[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961
+
+
+
+[@stdlib/stats/strided/dmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanwd
+
+[@stdlib/stats/strided/dmeanstdevwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanstdevwd
+
+[@stdlib/stats/strided/dmeanvar]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanvar
+
+[@stdlib/stats/strided/dvariancewd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dvariancewd
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.js
new file mode 100644
index 000000000000..5c23549538e3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 bench = require( '@stdlib/bench' );
+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' );
+var pkg = require( './../package.json' ).name;
+var dmeanvarwd = require( './../lib/dmeanvarwd.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out = new Float64Array( 2 );
+ var x = uniform( len, -10.0, 10.0, options );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ dmeanvarwd( x.length, 1, x, 1, out, 1 );
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..276dd765c006
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.native.js
@@ -0,0 +1,108 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+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' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dmeanvarwd = tryRequire( resolve( __dirname, './../lib/dmeanvarwd.native.js' ) );
+var opts = {
+ 'skip': ( dmeanvarwd instanceof Error )
+};
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out = new Float64Array( 2 );
+ var x = uniform( len, -10.0, 10.0, options );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ dmeanvarwd( x.length, 1, x, 1, out, 1 );
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+'::native:len='+len, opts, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.ndarray.js
new file mode 100644
index 000000000000..716c17cc192e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.ndarray.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 bench = require( '@stdlib/bench' );
+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' );
+var pkg = require( './../package.json' ).name;
+var dmeanvarwd = require( './../lib/ndarray.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out = new Float64Array( 2 );
+ var x = uniform( len, -10.0, 10.0, options );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':ndarray:len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.ndarray.native.js
new file mode 100644
index 000000000000..429af7c55380
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/benchmark.ndarray.native.js
@@ -0,0 +1,108 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+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' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dmeanvarwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+ 'skip': ( dmeanvarwd instanceof Error )
+};
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out = new Float64Array( 2 );
+ var x = uniform( len, -10.0, 10.0, options );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( out[ i%2 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+'::native:ndarray:len='+len, opts, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/c/Makefile
new file mode 100644
index 000000000000..0756dc7da20a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2026 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.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+ QUIET := @
+else
+ QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+ OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+ CC := $(C_COMPILER)
+else
+ CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+ -std=c99 \
+ -O3 \
+ -Wall \
+ -pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+ fPIC ?=
+else
+ fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.length.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+ $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+ $(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+ $(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/c/benchmark.length.c
new file mode 100644
index 000000000000..9607cde3a587
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/benchmark/c/benchmark.length.c
@@ -0,0 +1,201 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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.
+*/
+
+#include "stdlib/stats/strided/dmeanvarwd.h"
+#include
+#include
+#include
+#include
+#include
+
+#define NAME "dmeanvarwd"
+#define ITERATIONS 1000000
+#define REPEATS 3
+#define MIN 1
+#define MAX 6
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+ printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total total number of tests
+* @param passing total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+ printf( "#\n" );
+ printf( "1..%d\n", total ); // TAP plan
+ printf( "# total %d\n", total );
+ printf( "# pass %d\n", passing );
+ printf( "#\n" );
+ printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param iterations number of iterations
+* @param elapsed elapsed time in seconds
+*/
+static void print_results( int iterations, double elapsed ) {
+ double rate = (double)iterations / elapsed;
+ printf( " ---\n" );
+ printf( " iterations: %d\n", iterations );
+ printf( " elapsed: %0.9f\n", elapsed );
+ printf( " rate: %0.9f\n", rate );
+ printf( " ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+ struct timeval now;
+ gettimeofday( &now, NULL );
+ return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [0,1).
+*
+* @return random number
+*/
+static double rand_double( void ) {
+ int r = rand();
+ return (double)r / ( (double)RAND_MAX + 1.0 );
+}
+
+/**
+* Runs a benchmark.
+*
+* @param iterations number of iterations
+* @param len array length
+* @return elapsed time in seconds
+*/
+static double benchmark1( 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_dmeanvarwd( len, 1, x, 1, out, 1 );
+ 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;
+}
+
+/**
+* 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_dmeanvarwd_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.
+*/
+int main( void ) {
+ double elapsed;
+ int count;
+ int iter;
+ int len;
+ int i;
+ int j;
+
+ // Use the current time to seed the random number generator:
+ srand( time( NULL ) );
+
+ print_version();
+ count = 0;
+ 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:len=%d\n", NAME, 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 );
+ }
+ }
+ print_summary( count, count );
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/binding.gyp
new file mode 100644
index 000000000000..0d6508a12e99
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2026 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.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+ # List of files to include in this file:
+ 'includes': [
+ './include.gypi',
+ ],
+
+ # Define variables to be used throughout the configuration for all targets:
+ 'variables': {
+ # Target name should match the add-on export name:
+ 'addon_target_name%': 'addon',
+
+ # Set variables based on the host OS:
+ 'conditions': [
+ [
+ 'OS=="win"',
+ {
+ # Define the object file suffix:
+ 'obj': 'obj',
+ },
+ {
+ # Define the object file suffix:
+ 'obj': 'o',
+ }
+ ], # end condition (OS=="win")
+ ], # end conditions
+ }, # end variables
+
+ # Define compile targets:
+ 'targets': [
+
+ # Target to generate an add-on:
+ {
+ # The target name should match the add-on export name:
+ 'target_name': '<(addon_target_name)',
+
+ # Define dependencies:
+ 'dependencies': [],
+
+ # Define directories which contain relevant include headers:
+ 'include_dirs': [
+ # Local include directory:
+ '<@(include_dirs)',
+ ],
+
+ # List of source files:
+ 'sources': [
+ '<@(src_files)',
+ ],
+
+ # Settings which should be applied when a target's object files are used as linker input:
+ 'link_settings': {
+ # Define libraries:
+ 'libraries': [
+ '<@(libraries)',
+ ],
+
+ # Define library directories:
+ 'library_dirs': [
+ '<@(library_dirs)',
+ ],
+ },
+
+ # C/C++ compiler flags:
+ 'cflags': [
+ # Enable commonly used warning options:
+ '-Wall',
+
+ # Aggressive optimization:
+ '-O3',
+ ],
+
+ # C specific compiler flags:
+ 'cflags_c': [
+ # Specify the C standard to which a program is expected to conform:
+ '-std=c99',
+ ],
+
+ # C++ specific compiler flags:
+ 'cflags_cpp': [
+ # Specify the C++ standard to which a program is expected to conform:
+ '-std=c++11',
+ ],
+
+ # Linker flags:
+ 'ldflags': [],
+
+ # Apply conditions based on the host OS:
+ 'conditions': [
+ [
+ 'OS=="mac"',
+ {
+ # Linker flags:
+ 'ldflags': [
+ '-undefined dynamic_lookup',
+ '-Wl,-no-pie',
+ '-Wl,-search_paths_first',
+ ],
+ },
+ ], # end condition (OS=="mac")
+ [
+ 'OS!="win"',
+ {
+ # C/C++ flags:
+ 'cflags': [
+ # Generate platform-independent code:
+ '-fPIC',
+ ],
+ },
+ ], # end condition (OS!="win")
+ ], # end conditions
+ }, # end target <(addon_target_name)
+
+ # Target to copy a generated add-on to a standard location:
+ {
+ 'target_name': 'copy_addon',
+
+ # Declare that the output of this target is not linked:
+ 'type': 'none',
+
+ # Define dependencies:
+ 'dependencies': [
+ # Require that the add-on be generated before building this target:
+ '<(addon_target_name)',
+ ],
+
+ # Define a list of actions:
+ 'actions': [
+ {
+ 'action_name': 'copy_addon',
+ 'message': 'Copying addon...',
+
+ # Explicitly list the inputs in the command-line invocation below:
+ 'inputs': [],
+
+ # Declare the expected outputs:
+ 'outputs': [
+ '<(addon_output_dir)/<(addon_target_name).node',
+ ],
+
+ # Define the command-line invocation:
+ 'action': [
+ 'cp',
+ '<(PRODUCT_DIR)/<(addon_target_name).node',
+ '<(addon_output_dir)/<(addon_target_name).node',
+ ],
+ },
+ ], # end actions
+ }, # end target copy_addon
+ ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_population_mean.svg b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_population_mean.svg
new file mode 100644
index 000000000000..4bbdf0d2a56f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_population_mean.svg
@@ -0,0 +1,42 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_population_variance.svg b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_population_variance.svg
new file mode 100644
index 000000000000..4130ba0750d2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_population_variance.svg
@@ -0,0 +1,54 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_sample_mean.svg
new file mode 100644
index 000000000000..aea7a5f6687a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_sample_mean.svg
@@ -0,0 +1,43 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_unbiased_sample_variance.svg b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_unbiased_sample_variance.svg
new file mode 100644
index 000000000000..1ae1283e7fb1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/img/equation_unbiased_sample_variance.svg
@@ -0,0 +1,61 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/repl.txt
new file mode 100644
index 000000000000..ce505e0a83d1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/repl.txt
@@ -0,0 +1,134 @@
+
+{{alias}}( N, c, x, strideX, out, strideOut )
+ Computes the mean and variance of a double-precision floating-point strided
+ array using Welford's algorithm.
+
+ 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.
+
+ If `N <= 0`, the function returns a mean and variance equal to `NaN`.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ c: number
+ 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 according to `N - c` where `c` corresponds to the
+ provided degrees of freedom adjustment. When computing the 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, 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: Float64Array
+ Input array.
+
+ strideX: integer
+ Stride length for `x`.
+
+ out: Float64Array
+ Output array.
+
+ strideOut: integer
+ Stride length for `out`.
+
+ Returns
+ -------
+ out: Float64Array
+ Output array.
+
+ Examples
+ --------
+ // Standard Usage:
+ > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+ > var out = new {{alias:@stdlib/array/float64}}( 2 );
+ > {{alias}}( x.length, 1, x, 1, out, 1 )
+ [ ~0.3333, ~4.3333 ]
+
+ // 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 );
+ > {{alias}}( 3, 1, x, 2, out, 1 )
+ [ ~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 );
+ > out = new {{alias:@stdlib/array/float64}}( 2 );
+ > {{alias}}( 3, 1, x1, 2, out, 1 )
+ [ ~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 Welford's algorithm 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
+ starting index.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ c: number
+ 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 according to `N - c` where `c` corresponds to the
+ provided degrees of freedom adjustment. When computing the 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, 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: Float64Array
+ Input array.
+
+ strideX: integer
+ Stride length for `x`.
+
+ offsetX: integer
+ Starting index for `x`.
+
+ out: Float64Array
+ Output array.
+
+ strideOut: integer
+ Stride length for `out`.
+
+ offsetOut: integer
+ Starting index for `out`.
+
+ Returns
+ -------
+ out: Float64Array
+ Output array.
+
+ Examples
+ --------
+ // Standard Usage:
+ > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+ > var out = new {{alias:@stdlib/array/float64}}( 2 );
+ > {{alias}}.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )
+ [ ~0.3333, ~4.3333 ]
+
+ // Using offset parameter:
+ > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );
+ > out = new {{alias:@stdlib/array/float64}}( 2 );
+ > {{alias}}.ndarray( 3, 1, x, 2, 1, out, 1, 0 )
+ [ ~0.3333, ~4.3333 ]
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/types/index.d.ts
new file mode 100644
index 000000000000..1dfed67dcd00
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/types/index.d.ts
@@ -0,0 +1,106 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Interface describing `dmeanvarwd`.
+*/
+interface Routine {
+ /**
+ * Computes the mean and variance of a double-precision floating-point strided array using Welford's algorithm.
+ *
+ * @param N - number of indexed elements
+ * @param correction - degrees of freedom adjustment
+ * @param x - input array
+ * @param strideX - `x` stride length
+ * @param out - output array
+ * @param strideOut - `out` stride length
+ * @returns output array
+ *
+ * @example
+ * var Float64Array = require( '@stdlib/array/float64' );
+ *
+ * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+ * var out = new Float64Array( 2 );
+ *
+ * var v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+ * // returns [ ~0.3333, ~4.3333 ]
+ */
+ ( N: number, correction: number, x: Float64Array, strideX: number, out: Float64Array, strideOut: number ): Float64Array;
+
+ /**
+ * Computes the mean and variance of a double-precision floating-point strided array using Welford's 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 - `x` starting index
+ * @param out - output array
+ * @param strideOut - `out` stride length
+ * @param offsetOut - `out` starting index
+ * @returns output array
+ *
+ * @example
+ * var Float64Array = require( '@stdlib/array/float64' );
+ *
+ * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+ * var out = new Float64Array( 2 );
+ *
+ * var v = dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, 0 );
+ * // returns [ ~0.3333, ~4.3333 ]
+ */
+ ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number, out: Float64Array, strideOut: number, offsetOut: number ): Float64Array;
+}
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using Welford's algorithm.
+*
+* @param N - number of indexed elements
+* @param correction - degrees of freedom adjustment
+* @param x - input array
+* @param strideX - `x` stride length
+* @param out - output array
+* @param strideOut - `out` stride length
+* @returns output array
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var out = new Float64Array( 2 );
+*
+* var v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+* // returns [ ~0.3333, ~4.3333 ]
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var out = new Float64Array( 2 );
+*
+* var v = dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, 0 );
+* // returns [ ~0.3333, ~4.3333 ]
+*/
+declare var dmeanvarwd: Routine;
+
+
+// EXPORTS //
+
+export = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/types/test.ts
new file mode 100644
index 000000000000..c7e35628f79b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/docs/types/test.ts
@@ -0,0 +1,280 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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.
+*/
+
+import dmeanvarwd = require( './index' );
+
+
+// TESTS //
+
+// The function returns a Float64Array...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd( x.length, 1, x, 1, out, 1 ); // $ExpectType Float64Array
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd( '10', 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( true, 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( false, 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( null, 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( undefined, 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( [], 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( {}, 1, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( ( x: number ): number => x, 1, x, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd( x.length, '10', x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, true, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, false, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, null, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, undefined, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, [], x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, {}, x, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, ( x: number ): number => x, x, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd( x.length, 1, 10, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, '10', 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, true, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, false, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, null, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, undefined, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, [ '1' ], 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, {}, 1, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, ( x: number ): number => x, 1, out, 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 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd( x.length, 1, x, '10', out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, true, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, false, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, null, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, undefined, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, [], out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, {}, out, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, ( x: number ): number => x, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+
+ dmeanvarwd( x.length, 1, x, 1, 10, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, '10', 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, true, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, false, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, null, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, undefined, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, [ '1' ], 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, {}, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, ( x: number ): number => x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a sixth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd( x.length, 1, x, 1, out, '10' ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, true ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, false ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, null ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, undefined ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, [] ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, {} ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd(); // $ExpectError
+ dmeanvarwd( x.length ); // $ExpectError
+ dmeanvarwd( x.length, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1 ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out ); // $ExpectError
+ dmeanvarwd( x.length, 1, x, 1, out, 1, 10 ); // $ExpectError
+}
+
+// Attached to main export is an `ndarray` method which returns a Float64Array...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, 0 ); // $ExpectType Float64Array
+}
+
+// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( '10', 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( true, 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( false, 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( null, 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( undefined, 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( [], 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( {}, 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( ( x: number ): number => x, 1, x, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, '10', x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, true, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, false, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, null, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, undefined, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, [], x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, {}, x, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, ( x: number ): number => x, x, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, 1, 10, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, '10', 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, true, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, false, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, null, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, undefined, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, {}, 1, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, ( x: number ): number => x, 1, 0, out, 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 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, 1, x, '10', 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, true, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, false, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, null, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, undefined, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, [], 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, {}, 0, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, ( x: number ): number => x, 0, out, 1, 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 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, 1, x, 1, '10', out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, true, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, false, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, null, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, undefined, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, [], out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, {}, out, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, 10, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, '10', 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, true, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, false, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, null, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, undefined, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, {}, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, '10', 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, true, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, false, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, null, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, undefined, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, [], 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, {}, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, '10' ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, true ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, false ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, null ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, undefined ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, [] ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, {} ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 2 );
+
+ dmeanvarwd.ndarray(); // $ExpectError
+ dmeanvarwd.ndarray( x.length ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1 ); // $ExpectError
+ dmeanvarwd.ndarray( x.length, 1, x, 1, 0, out, 1, 0, 10 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/c/Makefile
new file mode 100644
index 000000000000..c8f8e9a1517b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2026 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.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+ QUIET := @
+else
+ QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+ OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+ CC := $(C_COMPILER)
+else
+ CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+ -std=c99 \
+ -O3 \
+ -Wall \
+ -pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+ fPIC ?=
+else
+ fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+ $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+ $(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+ $(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/c/example.c
new file mode 100644
index 000000000000..4442b600f7f1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/c/example.c
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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.
+*/
+
+#include "stdlib/stats/strided/dmeanvarwd.h"
+#include
+
+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_dmeanvarwd( N, 1.0, x, strideX, out, strideOut );
+
+ // Print the result:
+ printf( "sample mean: %lf\n", out[ 0 ] );
+ printf( "sample variance: %lf\n", out[ 1 ] );
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/index.js
new file mode 100644
index 000000000000..219642a1546c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/examples/index.js
@@ -0,0 +1,32 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var dmeanvarwd = require( './../lib' );
+
+var x = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float64'
+});
+console.log( x );
+
+var out = new Float64Array( 2 );
+dmeanvarwd( x.length, 1, x, 1, out, 1 );
+console.log( out );
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/include.gypi b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/include.gypi
new file mode 100644
index 000000000000..bee8d41a2caf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2026 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.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+ # Define variables to be used throughout the configuration for all targets:
+ 'variables': {
+ # Source directory:
+ 'src_dir': './src',
+
+ # Include directories:
+ 'include_dirs': [
+ '[ ~0.3333, ~4.3333 ]
+*/
+function dmeanvarwd( N, correction, x, strideX, out, strideOut ) {
+ var ox = stride2offset( N, strideX );
+ var oo = ( strideOut >= 0 ) ? 0 : -strideOut;
+ ndarray( N, correction, x, strideX, ox, out, strideOut, oo );
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/dmeanvarwd.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/dmeanvarwd.native.js
new file mode 100644
index 000000000000..b85bacb809d8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/dmeanvarwd.native.js
@@ -0,0 +1,56 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using Welford's algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {Float64Array} x - input array
+* @param {integer} strideX - `x` stride length
+* @param {Float64Array} out - output array
+* @param {integer} strideOut - `out` stride length
+* @returns {Float64Array} output array
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var out = new Float64Array( 2 );
+*
+* var v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+* // returns [ ~0.3333, ~4.3333 ]
+*/
+function dmeanvarwd( N, correction, x, strideX, out, strideOut ) {
+ addon( N, correction, x, strideX, out, strideOut );
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/index.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/index.js
new file mode 100644
index 000000000000..bd15386ab47c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/index.js
@@ -0,0 +1,70 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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';
+
+/**
+* Compute the mean and variance of a double-precision floating-point strided array using Welford's algorithm.
+*
+* @module @stdlib/stats/strided/dmeanvarwd
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var dmeanvarwd = require( '@stdlib/stats/strided/dmeanvarwd' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var out = new Float64Array( 2 );
+*
+* var v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+* // returns [ ~0.3333, ~4.3333 ]
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var dmeanvarwd = require( '@stdlib/stats/strided/dmeanvarwd' );
+*
+* 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 v = dmeanvarwd.ndarray( 4, 1, x, 2, 1, out, 1, 0 );
+* // returns [ 1.25, 6.25 ]
+*/
+
+// MODULES //
+
+var join = require( 'path' ).join;
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isError = require( '@stdlib/assert/is-error' );
+var main = require( './main.js' );
+
+
+// MAIN //
+
+var dmeanvarwd;
+var tmp = tryRequire( join( __dirname, './native.js' ) );
+if ( isError( tmp ) ) {
+ dmeanvarwd = main;
+} else {
+ dmeanvarwd = tmp;
+}
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
+
+// exports: { "ndarray": "dmeanvarwd.ndarray" }
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/main.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/main.js
new file mode 100644
index 000000000000..c18252fd1cd6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/main.js
@@ -0,0 +1,35 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var dmeanvarwd = require( './dmeanvarwd.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( dmeanvarwd, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/native.js
new file mode 100644
index 000000000000..02a2bb26f8dd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/native.js
@@ -0,0 +1,35 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var dmeanvarwd = require( './dmeanvarwd.native.js' );
+var ndarray = require( './ndarray.native.js' );
+
+
+// MAIN //
+
+setReadOnly( dmeanvarwd, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/ndarray.js
new file mode 100644
index 000000000000..4b0e1a444776
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/ndarray.js
@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using Welford's algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {Float64Array} x - input array
+* @param {integer} strideX - `x` stride length
+* @param {NonNegativeInteger} offsetX - `x` starting index
+* @param {Float64Array} out - output array
+* @param {integer} strideOut - `out` stride length
+* @param {NonNegativeInteger} offsetOut - `out` starting index
+* @returns {Float64Array} output array
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+* var out = new Float64Array( 2 );
+*
+* var v = dmeanvarwd( 4, 1, x, 2, 1, out, 1, 0 );
+* // returns [ 1.25, 6.25 ]
+*/
+function dmeanvarwd( N, correction, x, strideX, offsetX, out, strideOut, offsetOut ) { // eslint-disable-line max-len
+ var mu;
+ var ix;
+ var io;
+ var M2;
+ var M;
+ var d;
+ var c;
+ var n;
+ var i;
+
+ ix = offsetX;
+ io = offsetOut;
+ 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, offsetX ) / 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));
+ }
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/ndarray.native.js
new file mode 100644
index 000000000000..1ca1d7c04c90
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/lib/ndarray.native.js
@@ -0,0 +1,58 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using Welford's algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {Float64Array} x - input array
+* @param {integer} strideX - `x` stride length
+* @param {NonNegativeInteger} offsetX - `x` starting index
+* @param {Float64Array} out - output array
+* @param {integer} strideOut - `out` stride length
+* @param {NonNegativeInteger} offsetOut - `out` starting index
+* @returns {Float64Array} output array
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+* var out = new Float64Array( 2 );
+*
+* var v = dmeanvarwd( 4, 1, x, 2, 1, out, 1, 0 );
+* // returns [ 1.25, 6.25 ]
+*/
+function dmeanvarwd( N, correction, x, strideX, offsetX, out, strideOut, offsetOut ) { // eslint-disable-line max-len
+ addon.ndarray( N, correction, x, strideX, offsetX, out, strideOut, offsetOut ); // eslint-disable-line max-len
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = dmeanvarwd;
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/manifest.json b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/manifest.json
new file mode 100644
index 000000000000..02e992690462
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/manifest.json
@@ -0,0 +1,107 @@
+{
+ "options": {
+ "task": "build",
+ "wasm": false
+ },
+ "fields": [
+ {
+ "field": "src",
+ "resolve": true,
+ "relative": true
+ },
+ {
+ "field": "include",
+ "resolve": true,
+ "relative": true
+ },
+ {
+ "field": "libraries",
+ "resolve": false,
+ "relative": false
+ },
+ {
+ "field": "libpath",
+ "resolve": true,
+ "relative": false
+ }
+ ],
+ "confs": [
+ {
+ "task": "build",
+ "wasm": false,
+ "src": [
+ "./src/main.c"
+ ],
+ "include": [
+ "./include"
+ ],
+ "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"
+ ]
+ },
+ {
+ "task": "benchmark",
+ "wasm": false,
+ "src": [
+ "./src/main.c"
+ ],
+ "include": [
+ "./include"
+ ],
+ "libraries": [],
+ "libpath": [],
+ "dependencies": [
+ "@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": [],
+ "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/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/strided/dmeanvarwd/package.json b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/package.json
new file mode 100644
index 000000000000..d960fdbcfa6f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/package.json
@@ -0,0 +1,85 @@
+{
+ "name": "@stdlib/stats/strided/dmeanvarwd",
+ "version": "0.0.0",
+ "description": "Calculate the mean and variance of a double-precision floating-point strided array using Welford's algorithm.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "browser": "./lib/main.js",
+ "gypfile": true,
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "include": "./include",
+ "lib": "./lib",
+ "src": "./src",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "mean",
+ "arithmetic mean",
+ "average",
+ "avg",
+ "central tendency",
+ "variance",
+ "var",
+ "deviation",
+ "dispersion",
+ "sample variance",
+ "unbiased",
+ "stdev",
+ "std",
+ "standard deviation",
+ "strided",
+ "strided array",
+ "typed",
+ "array",
+ "float64",
+ "double",
+ "float64array"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/Makefile
new file mode 100644
index 000000000000..2caf905cedbe
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2026 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.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+ QUIET := @
+else
+ QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+ OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+ $(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/addon.c
new file mode 100644
index 000000000000..f9f78f500a11
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/addon.c
@@ -0,0 +1,68 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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.
+*/
+
+#include "stdlib/stats/strided/dmeanvarwd.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_double.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include
+
+/**
+* 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( napi_env env, napi_callback_info info ) {
+ STDLIB_NAPI_ARGV( env, info, argv, argc, 6 );
+ STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+ STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 );
+ STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 );
+ 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, 4 );
+ API_SUFFIX(stdlib_strided_dmeanvarwd)( N, correction, X, strideX, Out, strideOut );
+ return NULL;
+}
+
+/**
+* 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_dmeanvarwd_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/strided/dmeanvarwd/src/main.c b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/main.c
new file mode 100644
index 000000000000..184f79357a69
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/src/main.c
@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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.
+*/
+
+#include "stdlib/stats/strided/dmeanvarwd.h"
+#include "stdlib/blas/ext/base/dsumpw.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 Welford's algorithm.
+*
+* @param N number of indexed elements
+* @param correction degrees of freedom adjustment
+* @param X input array
+* @param strideX X stride length
+* @param Out output array
+* @param strideOut Out stride length
+*/
+void API_SUFFIX(stdlib_strided_dmeanvarwd)( 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_dmeanvarwd_ndarray)( N, correction, X, strideX, ox, Out, strideOut, oo );
+ return;
+}
+
+/**
+* Computes the mean and variance of a double-precision floating-point strided array using Welford's 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_dmeanvarwd_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;
+ double M;
+ double d;
+ double c;
+ double n;
+
+ ix = offsetX;
+ io = offsetOut;
+ if ( N <= 0 ) {
+ Out[ io ] = 0.0 / 0.0; // NaN
+ Out[ io+strideOut ] = 0.0 / 0.0; // NaN
+ return;
+ }
+ dN = (double)N;
+ n = dN - correction;
+ if ( N == 1 || strideX == 0 ) {
+ Out[ io ] = X[ ix ];
+ if ( n <= 0.0 ) {
+ Out[ io+strideOut ] = 0.0 / 0.0; // NaN
+ } else {
+ Out[ io+strideOut ] = 0.0;
+ }
+ return;
+ }
+ // Compute an estimate for the mean:
+ 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;
+ }
+ // 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 / dN;
+
+ Out[ io ] = mu + c;
+ if ( n <= 0.0 ) {
+ Out[ io+strideOut ] = 0.0 / 0.0; // NaN
+ } else {
+ Out[ io+strideOut ] = (M2/n) - (c*(M/n));
+ }
+ return;
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.dmeanvarwd.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.dmeanvarwd.js
new file mode 100644
index 000000000000..2e809722c883
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.dmeanvarwd.js
@@ -0,0 +1,290 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var dmeanvarwd = require( './../lib/dmeanvarwd.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dmeanvarwd, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 6', function test( t ) {
+ t.strictEqual( dmeanvarwd.length, 6, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and population variance of a strided array', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, out, 1 );
+
+ expected = new Float64Array( [ 0.5, 53.5/x.length ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, out, 1 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, out, 1 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and sample variance of a strided array', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+
+ expected = new Float64Array( [ 0.5, 53.5/(x.length-1) ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` values', function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 0, 1, x, 1, out, 1 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( -1, 1, x, 1, out, 1 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), 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 expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 0, x, 1, out, 1 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns a variance equal to `NaN`', function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 1, x, 1, out, 1 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 0, out, 1 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 1, out, 1 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length+1, x, 1, out, 1 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports `stride` parameters', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 4, 1, x, 2, out, 2 );
+
+ expected = new Float64Array( [ 1.25, 0.0, 6.25, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports negative `stride` parameters', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 4, 1, x, -2, out, -2 );
+
+ expected = new Float64Array( [ 6.25, 0.0, 1.25, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns an arithmetic mean equal to the first element and a variance of `0`', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+ out = new Float64Array( 2 );
+
+ v = dmeanvarwd( x.length, 1, x, 0, out, 1 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports view offsets', function test( t ) {
+ var expected0;
+ var expected1;
+ var out0;
+ var out1;
+ 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
+ ]);
+ out0 = new Float64Array( 4 );
+
+ 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
+
+ v = dmeanvarwd( 4, 1, x1, 2, out1, 1 );
+
+ expected0 = new Float64Array( [ 0.0, 0.0, 1.25, 6.25 ] );
+ expected1 = new Float64Array( [ 1.25, 6.25 ] );
+
+ t.deepEqual( out0, expected0, 'returns expected value' );
+ t.deepEqual( v, expected1, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.dmeanvarwd.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.dmeanvarwd.native.js
new file mode 100644
index 000000000000..cad9f8675b00
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.dmeanvarwd.native.js
@@ -0,0 +1,299 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// VARIABLES //
+
+var dmeanvarwd = tryRequire( resolve( __dirname, './../lib/dmeanvarwd.native.js' ) );
+var opts = {
+ 'skip': ( dmeanvarwd instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dmeanvarwd, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 6', opts, function test( t ) {
+ t.strictEqual( dmeanvarwd.length, 6, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and population variance of a strided array', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, out, 1 );
+
+ expected = new Float64Array( [ 0.5, 53.5/x.length ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, out, 1 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, out, 1 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and sample variance of a strided array', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+
+ expected = new Float64Array( [ 0.5, 53.5/(x.length-1) ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, out, 1 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` values', opts, function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 0, 1, x, 1, out, 1 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( -1, 1, x, 1, out, 1 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0`', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 0, x, 1, out, 1 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns a variance equal to `NaN`', opts, function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 1, x, 1, out, 1 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 0, out, 1 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 1, out, 1 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length+1, x, 1, out, 1 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports `stride` parameters', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 4, 1, x, 2, out, 2 );
+
+ expected = new Float64Array( [ 1.25, 0.0, 6.25, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 4, 1, x, -2, out, -2 );
+
+ expected = new Float64Array( [ 6.25, 0.0, 1.25, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns an arithmetic mean equal to the first element and a variance of `0`', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+ out = new Float64Array( 2 );
+
+ v = dmeanvarwd( x.length, 1, x, 0, out, 1 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports view offsets', opts, function test( t ) {
+ var expected0;
+ var expected1;
+ var out0;
+ var out1;
+ 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
+ ]);
+ out0 = new Float64Array( 4 );
+
+ 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
+
+ v = dmeanvarwd( 4, 1, x1, 2, out1, 1 );
+
+ expected0 = new Float64Array( [ 0.0, 0.0, 1.25, 6.25 ] );
+ expected1 = new Float64Array( [ 1.25, 6.25 ] );
+
+ t.deepEqual( out0, expected0, 'returns expected value' );
+ t.deepEqual( v, expected1, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.js
new file mode 100644
index 000000000000..d60c6df40a9c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.js
@@ -0,0 +1,82 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 proxyquire = require( 'proxyquire' );
+var IS_BROWSER = require( '@stdlib/assert/is-browser' );
+var dmeanvarwd = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+ 'skip': IS_BROWSER
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dmeanvarwd, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) {
+ t.strictEqual( typeof dmeanvarwd.ndarray, 'function', 'method is a function' );
+ t.end();
+});
+
+tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) {
+ var dmeanvarwd = proxyquire( './../lib', {
+ '@stdlib/utils/try-require': tryRequire
+ });
+
+ t.strictEqual( dmeanvarwd, mock, 'returns expected value' );
+ t.end();
+
+ function tryRequire() {
+ return mock;
+ }
+
+ function mock() {
+ // Mock...
+ }
+});
+
+tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) {
+ var dmeanvarwd;
+ var main;
+
+ main = require( './../lib/dmeanvarwd.js' );
+
+ dmeanvarwd = proxyquire( './../lib', {
+ '@stdlib/utils/try-require': tryRequire
+ });
+
+ t.strictEqual( dmeanvarwd, main, 'returns expected value' );
+ t.end();
+
+ function tryRequire() {
+ return new Error( 'Cannot find module' );
+ }
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.ndarray.js
new file mode 100644
index 000000000000..7f4f42dce83a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.ndarray.js
@@ -0,0 +1,280 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var dmeanvarwd = require( './../lib/ndarray.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dmeanvarwd, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 8', function test( t ) {
+ t.strictEqual( dmeanvarwd.length, 8, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and population variance of a strided array', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 0.5, 53.5/x.length ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and sample variance of a strided array', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 0.5, 53.5/(x.length-1) ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` values', function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 0, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( -1, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), 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 expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 0, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns a variance equal to `NaN`', function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 0, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length+1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports `stride` parameters', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 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' );
+
+ t.end();
+});
+
+tape( 'the function supports negative `stride` parameters', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 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' );
+
+ t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns an arithmetic mean equal to the first element and a variance of `0`', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+ out = new Float64Array( 2 );
+
+ v = dmeanvarwd( x.length, 1, x, 0, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports `offset` parameters', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 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' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.ndarray.native.js
new file mode 100644
index 000000000000..032b021d561a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarwd/test/test.ndarray.native.js
@@ -0,0 +1,289 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// VARIABLES //
+
+var dmeanvarwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+ 'skip': ( dmeanvarwd instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dmeanvarwd, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 8', opts, function test( t ) {
+ t.strictEqual( dmeanvarwd.length, 8, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and population variance of a strided array', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 0.5, 53.5/x.length ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 0, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the arithmetic mean and sample variance of a strided array', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 0.5, 53.5/(x.length-1) ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ -4.0, 0.0 ] );
+ t.strictEqual( v, out, 'returns expected value' );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, 4.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v, out, 'returns expected value' );
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` values', opts, function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 0, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( -1, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( isnan( v[ 0 ] ), true, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0`', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 0, x, 1, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns a variance equal to `NaN`', opts, function test( t ) {
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( 1, 1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 0, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 1.0, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ out = new Float64Array( 2 );
+ v = dmeanvarwd( x.length, x.length+1, x, 1, 0, out, 1, 0 );
+
+ t.strictEqual( v[ 0 ], 0.5, 'returns expected value' );
+ t.strictEqual( isnan( v[ 1 ] ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports `stride` parameters', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 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' );
+
+ t.end();
+});
+
+tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 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' );
+
+ t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the function returns an arithmetic mean equal to the first element and a variance of `0`', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+ out = new Float64Array( 2 );
+
+ v = dmeanvarwd( x.length, 1, x, 0, 0, out, 1, 0 );
+
+ expected = new Float64Array( [ 1.0, 0.0 ] );
+ t.deepEqual( v, expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports `offset` parameters', opts, function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ]);
+ out = new Float64Array( 4 );
+
+ v = dmeanvarwd( 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' );
+
+ t.end();
+});