diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/README.md
new file mode 100644
index 000000000000..f01183bace76
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/README.md
@@ -0,0 +1,203 @@
+
+
+# variancewd
+
+> Calculate the [variance][variance] of a one-dimensional ndarray 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 an **uncorrected sample variance**. To compute a **corrected 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 variancewd = require( '@stdlib/stats/base/ndarray/variancewd' );
+```
+
+#### variancewd( arrays )
+
+Computes the [variance][variance] of a one-dimensional ndarray using Welford's algorithm.
+
+```javascript
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+
+var xbuf = [ 1.0, -2.0, 2.0 ];
+var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
+var correction = scalar2ndarray( 1.0, opts );
+
+var v = variancewd( [ x, correction ] );
+// returns ~4.3333
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing two elements: a one-dimensional input ndarray and a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `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 corrected 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).
+
+
+
+
+
+
+
+## Notes
+
+- If provided an empty one-dimensional ndarray, the function returns `NaN`.
+- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var variancewd = require( '@stdlib/stats/base/ndarray/variancewd' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+var xbuf = discreteUniform( 10, -50, 50, opts );
+var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var correction = scalar2ndarray( 1.0, opts );
+var v = variancewd( [ x, correction ] );
+console.log( v );
+```
+
+
+
+
+
+* * *
+
+
+
+## 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].
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[variance]: https://en.wikipedia.org/wiki/Variance
+
+[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
+
+[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/benchmark/benchmark.js
new file mode 100644
index 000000000000..a266b66970d8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/benchmark/benchmark.js
@@ -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.
+*/
+
+'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 ndarray = require( '@stdlib/ndarray/base/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var variancewd = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var correction;
+ var xbuf;
+ var x;
+
+ xbuf = uniform( len, -10.0, 10.0, options );
+ x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+ correction = scalar2ndarray( 1.0, options );
+
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = variancewd( [ x, correction ] );
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( v ) ) {
+ 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( format( '%s:len=%d', pkg, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/img/equation_sample_mean.svg
new file mode 100644
index 000000000000..aea7a5f6687a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/img/equation_sample_mean.svg
@@ -0,0 +1,43 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/repl.txt
new file mode 100644
index 000000000000..15603bc9a2ed
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/repl.txt
@@ -0,0 +1,55 @@
+
+{{alias}}( arrays )
+ Computes the variance of a one-dimensional ndarray using
+ Welford's algorithm.
+
+ If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+ If `N - c` is less than or equal to `0` (where `N` corresponds to the number
+ of elements in the input ndarray and `c` corresponds to the provided degrees
+ of freedom adjustment), the function returns `NaN`.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing two elements: a one-dimensional input
+ ndarray and a zero-dimensional ndarray specifying the degrees of freedom
+ adjustment. Providing a non-zero degrees of freedom adjustment has the
+ effect of adjusting the divisor during the calculation of the variance
+ according to `N-c` where `N` is the number of elements in the
+ input ndarray and `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 corrected 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).
+
+ Returns
+ -------
+ out: number
+ The variance.
+
+ Examples
+ --------
+ // Create input ndarray:
+ > var xbuf = [ 1.0, -2.0, 2.0 ];
+ > var dt = 'generic';
+ > var sh = [ xbuf.length ];
+ > var st = [ 1 ];
+ > var oo = 0;
+ > var ord = 'row-major';
+ > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord );
+
+ // Create correction ndarray:
+ > var opts = { 'dtype': dt };
+ > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+
+ // Compute the variance:
+ > {{alias}}( [ x, correction ] )
+ ~4.3333
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/types/index.d.ts
new file mode 100644
index 000000000000..bd3db009b7c5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/types/index.d.ts
@@ -0,0 +1,52 @@
+/*
+* @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
+
+///
+
+import { typedndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the variancewd of a one-dimensional ndarray using Welford's algorithm.
+*
+* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment
+* @returns variance
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var opts = {
+* 'dtype': 'float64'
+* };
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
+* var correction = scalar2ndarray( 1.0, opts );
+*
+* var v = variancewd( [ x, correction ] );
+* // returns ~4.3333
+*/
+declare function variancewd = typedndarray>( arrays: [ T, T ] ): number;
+
+
+// EXPORTS //
+
+export = variancewd;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/types/test.ts
new file mode 100644
index 000000000000..9ce25bd03082
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/docs/types/test.ts
@@ -0,0 +1,65 @@
+/*
+* @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.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+import variancewd = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ const x = zeros( [ 10 ], {
+ 'dtype': 'float64'
+ });
+ const correction = scalar2ndarray( 1.0, {
+ 'dtype': 'float64'
+ });
+
+ variancewd( [ x, correction ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+ variancewd( '10' ); // $ExpectError
+ variancewd( 10 ); // $ExpectError
+ variancewd( true ); // $ExpectError
+ variancewd( false ); // $ExpectError
+ variancewd( null ); // $ExpectError
+ variancewd( undefined ); // $ExpectError
+ variancewd( [] ); // $ExpectError
+ variancewd( {} ); // $ExpectError
+ variancewd( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = zeros( [ 10 ], {
+ 'dtype': 'float64'
+ });
+ const correction = scalar2ndarray( 1.0, {
+ 'dtype': 'float64'
+ });
+
+ variancewd(); // $ExpectError
+ variancewd( [ x, correction ], 10 ); // $ExpectError
+}
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/examples/index.js
new file mode 100644
index 000000000000..62563c939c4e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/examples/index.js
@@ -0,0 +1,37 @@
+/**
+* @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 scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var variancewd = require( './../lib' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+var xbuf = discreteUniform( 10, -50, 50, opts );
+var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var correction = scalar2ndarray( 1.0, opts );
+var v = variancewd( [ x, correction ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/lib/index.js
new file mode 100644
index 000000000000..e16322031bd5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/lib/index.js
@@ -0,0 +1,54 @@
+/**
+* @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 variance of a one-dimensional ndarray using Welford's algorithm.
+*
+* @module @stdlib/stats/base/ndarray/variancewd
+*
+* @example
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var variancewd = require( '@stdlib/stats/base/ndarray/variancewd' );
+*
+* var opts = {
+* 'dtype': 'generic'
+* };
+*
+* // Define a one-dimensional input ndarray:
+* var xbuf = [ 1.0, -2.0, 2.0 ];
+* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
+*
+* // Specify the degrees of freedom adjustment:
+* var correction = scalar2ndarray( 1.0, opts );
+*
+* // Compute the variance:
+* var v = variancewd( [ x, correction ] );
+* // returns ~4.3333
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/lib/main.js
new file mode 100644
index 000000000000..1a26c0046bf1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancewd/lib/main.js
@@ -0,0 +1,69 @@
+/**
+* @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 numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
+var strided = require( '@stdlib/stats/strided/variancewd' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the variance of a one-dimensional ndarray using Welford's algorithm.
+*
+* @param {ArrayLikeObject