diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/README.md
new file mode 100644
index 000000000000..0a3605b4e0fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/README.md
@@ -0,0 +1,202 @@
+
+
+# dmeanstdev
+
+> Compute the [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] of a one-dimensional double-precision floating-point ndarray.
+
+
+
+The population [standard deviation][standard-deviation] of a finite size population of size `N` is given by
+
+
+
+```math
+\sigma = \sqrt{\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 [standard deviation][standard-deviation] 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 [standard deviation][standard-deviation], the result is biased and yields an **uncorrected sample standard deviation**. To compute a **corrected sample standard deviation** for a sample of size `n`,
+
+
+
+```math
+s = \sqrt{\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 standard deviation and population standard deviation. 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 dmeanstdev = require( '@stdlib/stats/base/ndarray/dmeanstdev' );
+```
+
+#### dmeanstdev( arrays )
+
+Computes the [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] of a one-dimensional double-precision floating-point ndarray.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+var out = new ndarray( opts.dtype, new Float64Array( 2 ), [ 2 ], [ 1 ], 0, 'row-major' );
+
+var correction = scalar2ndarray( 1.0, opts );
+
+var v = dmeanstdev( [ x, out, correction ] );
+// returns
+
+var arr = ndarray2array( v );
+// returns [ 2.5, ~1.2910 ]
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing the following ndarrays in order:
+
+ 1. a one-dimensional input ndarray.
+ 2. a one-dimensional output ndarray to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].
+ 3. a zero-dimensional ndarray specifying the degrees of freedom adjustment. Setting this to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this 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 computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.
+- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dmeanstdev = require( '@stdlib/stats/base/ndarray/dmeanstdev' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+var xbuf = discreteUniform( 10, -50, 50, opts );
+var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+var out = new ndarray( opts.dtype, new Float64Array( 2 ), [ 2 ], [ 1 ], 0, 'row-major' );
+var correction = scalar2ndarray( 1.0, opts );
+
+console.log( ndarray2array( x ) );
+
+var v = dmeanstdev( [ x, out, correction ] );
+console.log( v );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/benchmark/benchmark.js
new file mode 100644
index 000000000000..d179cac7e84d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/benchmark/benchmark.js
@@ -0,0 +1,107 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var 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 scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var zeros = require( '@stdlib/ndarray/base/zeros' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var dmeanstdev = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var correction;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = uniform( len, -10.0, 10.0, options );
+ x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+ out = zeros( options.dtype, [ 2 ], '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 = dmeanstdev( [ x, out, correction ] );
+ if ( isnan( v.get( i % 2 ) ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( v.get( 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/base/ndarray/dmeanstdev/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/img/equation_arithmetic_mean.svg
new file mode 100644
index 000000000000..c31439606fb6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/img/equation_arithmetic_mean.svg
@@ -0,0 +1,42 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/repl.txt
new file mode 100644
index 000000000000..abb8280739e8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/repl.txt
@@ -0,0 +1,51 @@
+
+{{alias}}( arrays )
+ Computes the mean and standard deviation of a one-dimensional double-
+ precision floating-point ndarray.
+
+ If provided an empty ndarray, the function returns `NaN` values.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing the following ndarrays in order:
+
+ - a one-dimensional input ndarray.
+ - a one-dimensional output ndarray to store the mean and standard
+ deviation.
+ - a zero-dimensional ndarray specifying the degrees of freedom
+ adjustment. Setting this to a value other than 0 has the effect of
+ adjusting the divisor during the calculation of the standard deviation
+ according to N-c where c corresponds to the provided degrees of freedom
+ adjustment. When computing the standard deviation of a population,
+ setting this to 0 is the standard choice (i.e., the provided array
+ contains data constituting an entire population). When computing the
+ corrected sample standard deviation, setting this 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: ndarray
+ An ndarray containing the mean and standard deviation.
+
+ Examples
+ --------
+ > var xbuf = new {{alias:@stdlib/array/float64}}( [ 2.0, 1.0, 2.0, -2.0 ] );
+ > var dt = 'float64';
+ > var sh = [ xbuf.length ];
+ > var sx = [ 1 ];
+ > var ox = 0;
+ > var ord = 'row-major';
+ > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+ > var o = new {{alias:@stdlib/array/float64}}( 2 );
+ > var out = new {{alias:@stdlib/ndarray/ctor}}( dt, o, [ 2 ], [ 1 ], ox, ord );
+ > var opts = { 'dtype': dt };
+ > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+ > {{alias}}( [ x, out, correction ] );
+ > var arr = {{alias:@stdlib/ndarray/to-array}}( out )
+ [ ~0.75, ~1.8930 ]
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/types/index.d.ts
new file mode 100644
index 000000000000..64e12e8872e1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/types/index.d.ts
@@ -0,0 +1,58 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+import { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the mean and standard deviation of a one-dimensional double-precision floating-point ndarray.
+*
+* @param arrays - array-like object containing an input ndarray, an output ndarray, and ndarray containing the degrees of freedom adjustment
+* @returns output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var dmeanstdev = require( '@stdlib/stats/base/ndarray/dmeanstdev' );
+*
+* var opts = {
+* 'dtype': 'float64'
+* };
+*
+* var xbuf = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+* var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' );
+* var out = new ndarray( opts.dtype, new Float64Array( 2 ), [ 2 ], [ 1 ], 0, 'row-major' );
+* var correction = scalar2ndarray( 1.0, opts );
+*
+* var v = dmeanstdev( [ x, out, correction ] );
+* // returns
+*
+* var arr = ndarray2array( v );
+* // returns [ ~1.25, ~2.5 ]
+*/
+declare function dmeanstdev( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray;
+
+
+// EXPORTS //
+
+export = dmeanstdev;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/types/test.ts
new file mode 100644
index 000000000000..ecd787c6fd23
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/types/test.ts
@@ -0,0 +1,72 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+import dmeanstdev = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ const x = zeros( [ 10 ], {
+ 'dtype': 'float64'
+ });
+ const out = zeros( [ 2 ], {
+ 'dtype': 'float64'
+ });
+ const correction = scalar2ndarray( 1.0, {
+ 'dtype': 'float64'
+ });
+
+ dmeanstdev( [ x, out, correction ] ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+ dmeanstdev( '10' ); // $ExpectError
+ dmeanstdev( 10 ); // $ExpectError
+ dmeanstdev( true ); // $ExpectError
+ dmeanstdev( false ); // $ExpectError
+ dmeanstdev( null ); // $ExpectError
+ dmeanstdev( undefined ); // $ExpectError
+ dmeanstdev( [] ); // $ExpectError
+ dmeanstdev( {} ); // $ExpectError
+ dmeanstdev( ( 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 out = zeros( [ 2 ], {
+ 'dtype': 'float64'
+ });
+ const correction = scalar2ndarray( 1.0, {
+ 'dtype': 'float64'
+ });
+
+ dmeanstdev(); // $ExpectError
+ dmeanstdev( [ x, out ] ); // $ExpectError
+ dmeanstdev( [ x, out, correction, correction ] ); // $ExpectError
+ dmeanstdev( [ x, out, correction ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/examples/index.js
new file mode 100644
index 000000000000..727296a34f86
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dmeanstdev = 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' );
+var out = new ndarray( opts.dtype, new Float64Array( 2 ), [ 2 ], [ 1 ], 0, 'row-major' );
+var correction = scalar2ndarray( 1.0, opts );
+
+console.log( ndarray2array( x ) );
+
+var v = dmeanstdev( [ x, out, correction ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/index.js
new file mode 100644
index 000000000000..64c083ea224c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/index.js
@@ -0,0 +1,56 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the mean and standard deviation of a one-dimensional double-precision floating-point ndarray.
+*
+* @module @stdlib/stats/base/ndarray/dmeanstdev
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var dmeanstdev = require( '@stdlib/stats/base/ndarray/dmeanstdev' );
+*
+* var opts = {
+* 'dtype': 'float64'
+* };
+*
+* var xbuf = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+* var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' );
+* var out = new ndarray( opts.dtype, new Float64Array( 2 ), [ 2 ], [ 1 ], 0, 'row-major' );
+* var correction = scalar2ndarray( 1.0, opts );
+*
+* var v = dmeanstdev( [ x, out, correction ] );
+* // returns
+*
+* var arr = ndarray2array( v );
+* // returns [ ~1.25, ~2.5 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/main.js
new file mode 100644
index 000000000000..7ad2508e6d7d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/main.js
@@ -0,0 +1,78 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var 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/dmeanstdev' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the mean and standard deviation of a one-dimensional double-precision floating-point ndarray.
+*
+* @param {ArrayLikeObject