diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/README.md
new file mode 100644
index 000000000000..3d408ccb50f2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/README.md
@@ -0,0 +1,186 @@
+
+
+# dztest2
+
+> Compute a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.
+
+
+
+A Z-test commonly refers to a two-sample location test which compares the means of two independent sets of measurements `X` and `Y` when the population standard deviations are known. A Z-test supports testing three different null hypotheses `H0`:
+
+- `H0: μX - μY ≥ Δ` versus the alternative hypothesis `H1: μX - μY < Δ`.
+- `H0: μX - μY ≤ Δ` versus the alternative hypothesis `H1: μX - μY > Δ`.
+- `H0: μX - μY = Δ` versus the alternative hypothesis `H1: μX - μY ≠ Δ`.
+
+Here, `μX` and `μY` are the true population means of samples `X` and `Y`, respectively, and `Δ` is the hypothesized difference in means (typically `0` by default).
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var dztest2 = require( '@stdlib/stats/base/ndarray/dztest2' );
+```
+
+#### dztest2( arrays )
+
+Computes a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.
+
+```javascript
+var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
+var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' );
+var structFactory = require( '@stdlib/array/struct-factory' );
+var Float64Array = require( '@stdlib/array/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+var xbuf = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
+var x = new ndarray( opts.dtype, xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+
+var ybuf = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
+var y = new ndarray( opts.dtype, ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
+
+var alt = scalar2ndarray( resolveEnum( 'two-sided' ), {
+ 'dtype': 'int8'
+});
+var alpha = scalar2ndarray( 0.05, opts );
+var diff = scalar2ndarray( 0.0, opts );
+var sigmax = scalar2ndarray( 1.0, opts );
+var sigmay = scalar2ndarray( 2.0, opts );
+
+var ResultsArray = structFactory( Float64Results );
+var out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );
+
+var v = dztest2( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+
+var bool = ( v === out );
+// returns true
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing the following ndarrays in order:
+
+ 1. first one-dimensional input ndarray.
+ 2. second one-dimensional input ndarray.
+ 3. a zero-dimensional output ndarray containing a [results object][@stdlib/stats/base/ztest/two-sample/results/float64].
+ 4. a zero-dimensional ndarray specifying the alternative hypothesis.
+ 5. a zero-dimensional ndarray specifying the significance level.
+ 6. a zero-dimensional ndarray specifying the difference in means under the null hypothesis.
+ 7. a zero-dimensional ndarray specifying the known standard deviation of the first one-dimensional input ndarray.
+ 8. a zero-dimensional ndarray specifying the known standard deviation of the second one-dimensional input ndarray.
+
+
+
+
+
+
+
+## Notes
+
+- As a general rule of thumb, a Z-test is most reliable for sample sizes greater than `50`. For smaller sample sizes or when the standard deviation is unknown, prefer a t-test.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
+var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' );
+var structFactory = require( '@stdlib/array/struct-factory' );
+var normal = require( '@stdlib/random/array/normal' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dztest2 = require( '@stdlib/stats/base/ndarray/dztest2' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+// Create one-dimensional ndarrays containing pseudorandom numbers drawn from a normal distribution:
+var xbuf = normal( 100, 0.0, 1.0, opts );
+var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var ybuf = normal( 100, 0.0, 1.0, opts );
+var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( y ) );
+
+// Specify the alternative hypothesis:
+var alt = scalar2ndarray( resolveEnum( 'two-sided' ), {
+ 'dtype': 'int8'
+});
+
+// Specify the significance level:
+var alpha = scalar2ndarray( 0.05, opts );
+
+// Specify the difference in means under the null hypothesis:
+var diff = scalar2ndarray( 0.0, opts );
+
+// Specify the known standard deviations:
+var sigmax = scalar2ndarray( 1.0, opts );
+var sigmay = scalar2ndarray( 1.0, opts );
+
+// Create a zero-dimensional results ndarray:
+var ResultsArray = structFactory( Float64Results );
+var out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );
+
+// Perform a Z-test:
+var v = dztest2( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+console.log( v.get().toString() );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[@stdlib/stats/base/ztest/two-sample/results/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ztest/two-sample/results/float64
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js
new file mode 100644
index 000000000000..2d92d940232f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js
@@ -0,0 +1,128 @@
+/**
+* @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 normal = require( '@stdlib/random/array/normal' );
+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/base/from-scalar' );
+var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
+var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' );
+var structFactory = require( '@stdlib/array/struct-factory' );
+var pkg = require( './../package.json' ).name;
+var dztest2 = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+var ResultsArray = structFactory( Float64Results );
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var sigmax;
+ var sigmay;
+ var alpha;
+ var diff;
+ var xbuf;
+ var ybuf;
+ var obuf;
+ var out;
+ var alt;
+ var x;
+ var y;
+
+ xbuf = normal( len, 0.0, 1.0, options );
+ x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+ ybuf = normal( len, 0.0, 1.0, options );
+ y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' );
+
+ obuf = new ResultsArray( 1 );
+ out = new ndarray( Float64Results, obuf, [], [ 0 ], 0, 'row-major' );
+
+ alt = scalar2ndarray( resolveEnum( 'two-sided' ), 'int8', 'row-major' );
+ alpha = scalar2ndarray( 0.05, options.dtype, 'row-major' );
+ diff = scalar2ndarray( 0.0, options.dtype, 'row-major' );
+ sigmax = scalar2ndarray( 1.0, options.dtype, 'row-major' );
+ sigmay = scalar2ndarray( 1.0, options.dtype, 'row-major' );
+
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = dztest2( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( isnan( v.get().statistic ) || isnan( v.get().pValue ) ) {
+ 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/dztest2/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/repl.txt
new file mode 100644
index 000000000000..801ebc77d783
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/repl.txt
@@ -0,0 +1,69 @@
+
+{{alias}}( arrays )
+ Computes a two-sample Z-test for two one-dimensional double-precision
+ floating-point ndarrays.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing the following ndarrays in order:
+
+ - first one-dimensional input ndarray.
+ - second one-dimensional input ndarray.
+ - a zero-dimensional output ndarray containing a results object.
+ - a zero-dimensional ndarray specifying the alternative hypothesis.
+ - a zero-dimensional ndarray specifying the significance level.
+ - a zero-dimensional ndarray specifying the difference in means under
+ the null hypothesis.
+ - a zero-dimensional ndarray specifying the known standard deviation of
+ the first one-dimensional input ndarray.
+ - a zero-dimensional ndarray specifying the known standard deviation of
+ the second one-dimensional input ndarray.
+
+ Returns
+ -------
+ out: ndarray
+ Output ndarray.
+
+ Examples
+ --------
+ // Create input ndarrays:
+ > var xbuf = new {{alias:@stdlib/array/float64}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
+ > var ybuf = new {{alias:@stdlib/array/float64}}( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
+ > var dt = 'float64';
+ > 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 );
+ > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord );
+
+ // Create the output ndarray:
+ > var S = {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}};
+ > var Results = {{alias:@stdlib/array/struct-factory}}( S );
+ > var obuf = new Results( 1 );
+ > var out = new {{alias:@stdlib/ndarray/ctor}}( S, obuf, [], [ 0 ], 0, ord );
+
+ // Specify the alternative hypothesis:
+ > var alt = {{alias:@stdlib/ndarray/from-scalar}}( 'two-sided' );
+
+ // Specify the significance level:
+ > var opts = { 'dtype': dt };
+ > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 0.05, opts );
+
+ // Specify the difference in means under the null hypothesis:
+ > var diff = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, opts );
+
+ // Specify the known standard deviations:
+ > var sigmax = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+ > var sigmay = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts );
+
+ // Perform a Z-test:
+ > {{alias}}( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+
+ // Print the results:
+ > out.get().toString()
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts
new file mode 100644
index 000000000000..90fb8c60dfb5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts
@@ -0,0 +1,93 @@
+/*
+* @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, ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.
+*
+* ## Notes
+*
+* - The function expects the following ndarrays in order:
+*
+* - first one-dimensional input ndarray.
+* - second one-dimensional input ndarray.
+* - a zero-dimensional output ndarray containing a results object.
+* - a zero-dimensional ndarray specifying the alternative hypothesis.
+* - a zero-dimensional ndarray specifying the significance level.
+* - a zero-dimensional ndarray specifying the difference in means under the null hypothesis.
+* - a zero-dimensional ndarray specifying the known standard deviation of the first one-dimensional input ndarray.
+* - a zero-dimensional ndarray specifying the known standard deviation of the second one-dimensional input ndarray.
+*
+* @param arrays - array-like object containing ndarrays
+* @returns output ndarray
+*
+* @example
+* var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
+* var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' );
+* var structFactory = require( '@stdlib/array/struct-factory' );
+* var Float64Array = require( '@stdlib/array/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* var opts = {
+* 'dtype': 'float64'
+* };
+*
+* // Define one-dimensional input ndarrays:
+* var xbuf = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
+* var x = new ndarray( opts.dtype, xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
+* var y = new ndarray( opts.dtype, ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
+*
+* // Specify the alternative hypothesis:
+* var alt = scalar2ndarray( resolveEnum( 'two-sided' ), {
+* 'dtype': 'int8'
+* });
+*
+* // Specify the significance level:
+* var alpha = scalar2ndarray( 0.05, opts );
+*
+* // Specify the difference in means under the null hypothesis:
+* var diff = scalar2ndarray( 0.0, opts );
+*
+* // Specify the known standard deviations:
+* var sigmax = scalar2ndarray( 1.0, opts );
+* var sigmay = scalar2ndarray( 2.0, opts );
+*
+* // Create a zero-dimensional results ndarray:
+* var ResultsArray = structFactory( Float64Results );
+* var out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );
+*
+* // Perform a Z-test:
+* var v = dztest2( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+* // returns
+*
+* console.log( v.get().toString() );
+*/
+declare function dztest2( arrays: [ float64ndarray, float64ndarray, T, float64ndarray, float64ndarray, float64ndarray, float64ndarray, float64ndarray ] ): T;
+
+
+// EXPORTS //
+
+export = dztest2;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/test.ts
new file mode 100644
index 000000000000..6eba30b6b10e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @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 dztest2 = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ const x = zeros( [ 10 ], {
+ 'dtype': 'float64'
+ });
+
+ dztest2( [ x, x, x, x, x, x, x, x ] ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+ dztest2( '10' ); // $ExpectError
+ dztest2( 10 ); // $ExpectError
+ dztest2( true ); // $ExpectError
+ dztest2( false ); // $ExpectError
+ dztest2( null ); // $ExpectError
+ dztest2( undefined ); // $ExpectError
+ dztest2( [] ); // $ExpectError
+ dztest2( {} ); // $ExpectError
+ dztest2( ( 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'
+ });
+
+ dztest2(); // $ExpectError
+ dztest2( [ x, x, x, x, x, x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/examples/index.js
new file mode 100644
index 000000000000..fc77ff17d175
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/examples/index.js
@@ -0,0 +1,64 @@
+/**
+* @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 Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
+var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' );
+var structFactory = require( '@stdlib/array/struct-factory' );
+var normal = require( '@stdlib/random/array/normal' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dztest2 = require( './../lib' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+
+// Create one-dimensional ndarrays containing pseudorandom numbers drawn from a normal distribution:
+var xbuf = normal( 100, 0.0, 1.0, opts );
+var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var ybuf = normal( 100, 0.0, 1.0, opts );
+var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( y ) );
+
+// Specify the alternative hypothesis:
+var alt = scalar2ndarray( resolveEnum( 'two-sided' ), {
+ 'dtype': 'int8'
+});
+
+// Specify the significance level:
+var alpha = scalar2ndarray( 0.05, opts );
+
+// Specify the difference in means under the null hypothesis:
+var diff = scalar2ndarray( 0.0, opts );
+
+// Specify the known standard deviations:
+var sigmax = scalar2ndarray( 1.0, opts );
+var sigmay = scalar2ndarray( 1.0, opts );
+
+// Create a zero-dimensional results ndarray:
+var ResultsArray = structFactory( Float64Results );
+var out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );
+
+// Perform a Z-test:
+var v = dztest2( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+console.log( v.get().toString() );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/lib/index.js
new file mode 100644
index 000000000000..4179b4dde936
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/lib/index.js
@@ -0,0 +1,79 @@
+/**
+* @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 a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.
+*
+* @module @stdlib/stats/base/ndarray/dztest2
+*
+* @example
+* var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
+* var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' );
+* var structFactory = require( '@stdlib/array/struct-factory' );
+* var Float64Array = require( '@stdlib/array/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var dztest2 = require( '@stdlib/stats/base/ndarray/dztest2' );
+*
+* var opts = {
+* 'dtype': 'float64'
+* };
+*
+* // Define one-dimensional input ndarrays:
+* var xbuf = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
+* var x = new ndarray( opts.dtype, xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
+* var y = new ndarray( opts.dtype, ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
+*
+* // Specify the alternative hypothesis:
+* var alt = scalar2ndarray( resolveEnum( 'two-sided' ), {
+* 'dtype': 'int8'
+* });
+*
+* // Specify the significance level:
+* var alpha = scalar2ndarray( 0.05, opts );
+*
+* // Specify the difference in means under the null hypothesis:
+* var diff = scalar2ndarray( 0.0, opts );
+*
+* // Specify the known standard deviations:
+* var sigmax = scalar2ndarray( 1.0, opts );
+* var sigmay = scalar2ndarray( 2.0, opts );
+*
+* // Create a zero-dimensional results ndarray:
+* var ResultsArray = structFactory( Float64Results );
+* var out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );
+*
+* // Perform a Z-test:
+* var v = dztest2( [ x, y, out, alt, alpha, diff, sigmax, sigmay ] );
+* // returns
+*
+* console.log( v.get().toString() );
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/lib/main.js
new file mode 100644
index 000000000000..63f9ea68e489
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/lib/main.js
@@ -0,0 +1,124 @@
+/**
+* @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/dztest2' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.
+*
+* ## Notes
+*
+* - The function expects the following ndarrays in order:
+*
+* - first one-dimensional input ndarray.
+* - second one-dimensional input ndarray.
+* - a zero-dimensional output ndarray containing a results object.
+* - a zero-dimensional ndarray specifying the alternative hypothesis.
+* - a zero-dimensional ndarray specifying the significance level.
+* - a zero-dimensional ndarray specifying the difference in means under the null hypothesis.
+* - a zero-dimensional ndarray specifying the known standard deviation of the first one-dimensional input ndarray.
+* - a zero-dimensional ndarray specifying the known standard deviation of the second one-dimensional input ndarray.
+*
+* @param {ArrayLikeObject