diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/README.md b/lib/node_modules/@stdlib/stats/strided/covarmtk/README.md
new file mode 100644
index 000000000000..3948e3f20451
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/README.md
@@ -0,0 +1,258 @@
+
+
+
+
+# covarmtk
+
+> Calculate the [covariance][covariance] of two strided arrays provided known means and using a one-pass textbook algorithm.
+
+
+
+The population [covariance][covariance] of two finite size populations of size `N` is given by
+
+
+
+```math
+\mathop{\mathrm{cov_N}} = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu_x)(y_i - \mu_y)
+```
+
+
+
+where the population means are given by
+
+
+
+```math
+\mu_x = \frac{1}{N} \sum_{i=0}^{N-1} x_i
+```
+
+
+
+and
+
+
+
+```math
+\mu_y = \frac{1}{N} \sum_{i=0}^{N-1} y_i
+```
+
+
+
+Often in the analysis of data, the true population [covariance][covariance] is not known _a priori_ and must be estimated from samples drawn from population distributions. If one attempts to use the formula for the population [covariance][covariance], the result is biased and yields a **biased sample covariance**. To compute an **unbiased sample covariance** for samples of size `n`,
+
+
+
+```math
+\mathop{\mathrm{cov_n}} = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x}_n)(y_i - \bar{y}_n)
+```
+
+
+
+where sample means are given by
+
+
+
+```math
+\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i
+```
+
+
+
+and
+
+
+
+```math
+\bar{y} = \frac{1}{n} \sum_{i=0}^{n-1} y_i
+```
+
+
+
+The use of the term `n-1` is commonly referred to as Bessel's correction. Depending on the characteristics of the population distributions, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var covarmtk = require( '@stdlib/stats/strided/covarmtk' );
+```
+
+#### covarmtk( N, correction, meanx, x, strideX, meany, y, strideY )
+
+Computes the [covariance][covariance] of two strided arrays provided known means and using a one-pass textbook algorithm.
+
+```javascript
+var x = [ 1.0, -2.0, 2.0 ];
+var y = [ 2.0, -2.0, 1.0 ];
+
+var v = covarmtk( x.length, 1, 1.0/3.0, x, 1, 1.0/3.0, y, 1 );
+// returns ~3.8333
+```
+
+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 [covariance][covariance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the population [covariance][covariance], setting this parameter to `0` is the standard choice (i.e., the provided arrays contain data constituting entire populations). When computing the unbiased sample [covariance][covariance], setting this parameter to `1` is the standard choice (i.e., the provided arrays contain data sampled from larger populations; this is commonly referred to as Bessel's correction).
+- **meanx**: mean of `x`.
+- **x**: first input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
+- **strideX**: stride length for `x`.
+- **meany**: mean of `y`.
+- **y**: second input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
+- **strideY**: stride length for `y`.
+
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the [covariance][covariance] of every other element in `x` and `y`,
+
+```javascript
+var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
+var y = [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ];
+
+var v = covarmtk( 4, 1, 1.25, x, 2, 1.25, y, 2 );
+// returns 5.25
+```
+
+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 y0 = new Float64Array( [ 2.0, -2.0, 2.0, 1.0, -2.0, 4.0, 3.0, 2.0 ] );
+
+var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+var v = covarmtk( 4, 1, 1.25, x1, 2, 1.25, y1, 2 );
+// returns ~1.9167
+```
+
+#### covarmtk.ndarray( N, correction, meanx, x, strideX, offsetX, meany, y, strideY, offsetY )
+
+Computes the [covariance][covariance] of two strided arrays provided known means and using a one-pass textbook algorithm and alternative indexing semantics.
+
+```javascript
+var x = [ 1.0, -2.0, 2.0 ];
+var y = [ 2.0, -2.0, 1.0 ];
+
+var v = covarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0, 1.0/3.0, y, 1, 0 );
+// returns ~3.8333
+```
+
+The function has the following additional parameters:
+
+- **offsetX**: starting index for `x`.
+- **offsetY**: starting index for `y`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the [covariance][covariance] for every other element in `x` and `y` starting from the second element
+
+```javascript
+var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
+var y = [ -7.0, 2.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ];
+
+var v = covarmtk.ndarray( 4, 1, 1.25, x, 2, 1, 1.25, y, 2, 1 );
+// returns 6.0
+```
+
+
+
+
+
+
+
+## Notes
+
+- If `N <= 0`, both functions return `NaN`.
+- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), both functions return `NaN`.
+- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
+- Depending on the environment, the typed versions ([`dcovarmtk`][@stdlib/stats/strided/dcovarmtk], [`scovarmtk`][@stdlib/stats/strided/scovarmtk], etc.) are likely to be significantly more performant.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var covarmtk = require( '@stdlib/stats/strided/covarmtk' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+var x = discreteUniform( 10, -50, 50, opts );
+console.log( x );
+
+var y = discreteUniform( 10, -50, 50, opts );
+console.log( y );
+
+var v = covarmtk( x.length, 1, 0.0, x, 1, 0.0, y, 1 );
+console.log( v );
+```
+
+
+
+
+
+* * *
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[covariance]: https://en.wikipedia.org/wiki/Covariance
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array
+
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
+[@stdlib/stats/strided/dcovarmtk]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcovarmtk
+
+[@stdlib/stats/strided/scovarmtk]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/scovarmtk
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/benchmark/benchmark.js
new file mode 100644
index 000000000000..30e121615e27
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/benchmark/benchmark.js
@@ -0,0 +1,96 @@
+/**
+* @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 pkg = require( './../package.json' ).name;
+var covarmtk = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -10.0, 10.0, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, 1 );
+ 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( pkg+':len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/benchmark/benchmark.ndarray.js
new file mode 100644
index 000000000000..c1ef80d6b40c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/benchmark/benchmark.ndarray.js
@@ -0,0 +1,96 @@
+/**
+* @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 pkg = require( './../package.json' ).name;
+var covarmtk = require( './../lib/ndarray.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -10.0, 10.0, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = covarmtk( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 );
+ 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( pkg+':ndarray:len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/repl.txt
new file mode 100644
index 000000000000..ebc14ae6b848
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/repl.txt
@@ -0,0 +1,141 @@
+
+{{alias}}( N, correction, meanx, x, sx, meany, y, sy )
+ Computes the covariance of two strided arrays provided known means and
+ using a one-pass textbook 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 `NaN`.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ correction: 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 covariance according to `N - c` where `c` corresponds to the
+ provided degrees of freedom adjustment. When computing the population
+ covariance, setting this parameter to `0` is the standard choice (i.e.,
+ the provided arrays contain data constituting entire populations). When
+ computing the unbiased sample covariance, setting this parameter to `1`
+ is the standard choice (i.e., the provided array contains data sampled
+ from larger populations; this is commonly referred to as Bessel's
+ correction).
+
+ meanx: number
+ Mean of `x`.
+
+ x: Array|TypedArray
+ First input array.
+
+ sx: integer
+ Stride length of `x`.
+
+ meany: number
+ Mean of `y`.
+
+ y: Array|TypedArray
+ Second input array.
+
+ sy: integer
+ Stride length of `y`.
+
+ Returns
+ -------
+ out: number
+ The covariance.
+
+ Examples
+ --------
+ // Standard Usage:
+ > var x = [ 1.0, -2.0, 2.0 ];
+ > {{alias}}( x.length, 1, 1.0/3.0, x, 1, 1.0/3.0, x, 1 )
+ ~4.3333
+
+ // Using `N` and stride parameters:
+ > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];
+ > {{alias}}( 3, 1, 1.0/3.0, x, 2, 1.0/3.0, x, 2 )
+ ~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 );
+ > {{alias}}( 3, 1, 1.0/3.0, x1, 2, 1.0/3.0, x1, 2 )
+ ~4.3333
+
+
+{{alias}}.ndarray( N, correction, meanx, x, sx, ox, meany, y, sy, oy )
+ Computes the covariance of two strided arrays provided known means and
+ using a one-pass textbook algorithm and alternative indexing semantics.
+
+ While typed array views mandate a view offset based on the underlying
+ buffer, offset parameters support indexing semantics based on starting
+ indices.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ correction: 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 covariance according to `N - c` where `c` corresponds to the
+ provided degrees of freedom adjustment. When computing the population
+ covariance, setting this parameter to `0` is the standard choice (i.e.,
+ the provided arrays contain data constituting entire populations). When
+ computing the unbiased sample covariance, setting this parameter to `1`
+ is the standard choice (i.e., the provided array contains data sampled
+ from larger populations; this is commonly referred to as Bessel's
+ correction).
+
+ meanx: number
+ Mean of `x`.
+
+ x: Array|TypedArray
+ First input array.
+
+ sx: integer
+ Stride length of `x`.
+
+ ox: integer
+ Starting index of `x`.
+
+ meany: number
+ Mean of `y`.
+
+ y: Array|TypedArray
+ Second input array.
+
+ sy: integer
+ Stride length of `y`.
+
+ oy: integer
+ Starting index of `y`.
+
+ Returns
+ -------
+ out: number
+ The covariance.
+
+ Examples
+ --------
+ // Standard Usage:
+ > var x = [ 1.0, -2.0, 2.0 ];
+ > {{alias}}.ndarray( x.length, 1, 1.0/3.0, x, 1, 0, 1.0/3.0, x, 1, 0 )
+ ~4.3333
+
+ // Using offset parameters:
+ > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ];
+ > {{alias}}.ndarray( 3, 1, 1.0/3.0, x, 2, 1, 1.0/3.0, x, 2, 1 )
+ ~4.3333
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/types/index.d.ts
new file mode 100644
index 000000000000..4fe34cd33d54
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/types/index.d.ts
@@ -0,0 +1,113 @@
+/*
+* @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 { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
+
+/**
+* Input array.
+*/
+type InputArray = NumericArray | Collection | AccessorArrayLike;
+
+/**
+* Interface describing `covarmtk`.
+*/
+interface Routine {
+ /**
+ * Computes the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
+ *
+ * @param N - number of indexed elements
+ * @param correction - degrees of freedom adjustment
+ * @param meanx - mean of `x`
+ * @param x - first input array
+ * @param strideX - stride length of `x`
+ * @param meany - mean of `y`
+ * @param y - second input array
+ * @param strideY - stride length of `y`
+ * @returns covariance
+ *
+ * @example
+ * var x = [ 1.0, -2.0, 2.0 ];
+ * var y = [ 2.0, -2.0, 1.0 ];
+ *
+ * var v = covarmtk( x.length, 1, 1.0/3.0, x, 1, 1.0/3.0, y, 1 );
+ * // returns ~3.8333
+ */
+ ( N: number, correction: number, meanx: number, x: InputArray, strideX: number, meany: number, y: InputArray, strideY: number ): number;
+
+ /**
+ * Computes the covariance of two strided arrays provided known means and using a one-pass textbook algorithm and alternative indexing semantics.
+ *
+ * @param N - number of indexed elements
+ * @param correction - degrees of freedom adjustment
+ * @param meanx - mean of `x`
+ * @param x - first input array
+ * @param strideX - stride length of `x`
+ * @param offsetX - starting index of `x`
+ * @param meany - mean of `y`
+ * @param y - second input array
+ * @param strideY - stride length of `y`
+ * @param offsetY - starting index of `y`
+ * @returns covariance
+ *
+ * @example
+ * var x = [ 1.0, -2.0, 2.0 ];
+ * var y = [ 2.0, -2.0, 1.0 ];
+ *
+ * var v = covarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0, 1.0/3.0, y, 1, 0 );
+ * // returns ~3.8333
+ */
+ ndarray( N: number, correction: number, meanx: number, x: InputArray, strideX: number, offsetX: number, meany: number, y: InputArray, strideY: number, offsetY: number ): number;
+}
+
+/**
+* Computes the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
+*
+* @param N - number of indexed elements
+* @param correction - degrees of freedom adjustment
+* @param meanx - mean of `x`
+* @param x - first input array
+* @param strideX - stride length of `x`
+* @param meany - mean of `y`
+* @param y - second input array
+* @param strideY - stride length of `y`
+* @returns covariance
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+* var y = [ 2.0, -2.0, 1.0 ];
+*
+* var v = covarmtk( x.length, 1, 1.0/3.0, x, 1, 1.0/3.0, y, 1 );
+* // returns ~3.8333
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+* var y = [ 2.0, -2.0, 1.0 ];
+*
+* var v = covarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0, 1.0/3.0, y, 1, 0 );
+* // returns ~3.8333
+*/
+declare var covarmtk: Routine;
+
+
+// EXPORTS //
+
+export = covarmtk;
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/types/test.ts
new file mode 100644
index 000000000000..f1d9724759f3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/docs/types/test.ts
@@ -0,0 +1,327 @@
+/*
+* @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.
+*/
+
+import AccessorArray = require( '@stdlib/array/base/accessor' );
+import covarmtk = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectType number
+ covarmtk( x.length, 1, 0.0, new AccessorArray( x ), 1, 0.0, new AccessorArray( x ), 1 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( '10', 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( true, 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( false, 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( null, 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( undefined, 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( [], 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( {}, 1, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( ( x: number ): number => x, 1, 0.0, x, 1, 0.0, x, 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 );
+
+ covarmtk( x.length, '10', 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, true, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, false, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, null, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, undefined, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, [], 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, {}, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, ( x: number ): number => x, 0.0, x, 1, 0.0, x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( x.length, 1, '10', x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, true, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, false, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, null, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, undefined, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, [], x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, {}, x, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, ( x: number ): number => x, x, 1, 0.0, x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( x.length, 1, 0.0, 10, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, '10', 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, true, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, false, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, null, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, undefined, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, [ '1' ], 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, {}, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, ( x: number ): number => x, 1, 0.0, x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( x.length, 1, 0.0, x, '10', 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, true, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, false, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, null, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, undefined, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, [], 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, {}, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, ( x: number ): number => x, 0.0, 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 );
+
+ covarmtk( x.length, 1, 0.0, x, 1, '10', x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, true, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, false, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, null, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, undefined, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, [], x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, {}, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, ( x: number ): number => x, x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a seventh argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, 10, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, '10', 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, true, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, false, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, null, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, undefined, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, [ '1' ], 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, {}, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, ( x: number ): number => x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an eighth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, '10' ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, true ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, false ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, null ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, undefined ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, [] ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, {} ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, ( 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 );
+
+ covarmtk(); // $ExpectError
+ covarmtk( x.length ); // $ExpectError
+ covarmtk( x.length, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0 ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x ); // $ExpectError
+ covarmtk( x.length, 1, 0.0, x, 1, 0.0, x, 1, 0 ); // $ExpectError
+}
+
+// Attached to main export is an `ndarray` method which returns a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectType number
+ covarmtk.ndarray( x.length, 1, 0.0, new AccessorArray( x ), 1, 0, 0.0, new AccessorArray( x ), 1, 0 ); // $ExpectType number
+}
+
+// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( '10', 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( true, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( false, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( null, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( undefined, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( [], 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( {}, 1, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( ( x: number ): number => x, 1, 0.0, x, 1, 0, 0.0, x, 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 );
+
+ covarmtk.ndarray( x.length, '10', 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, true, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, false, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, null, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, undefined, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, [], 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, {}, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, ( x: number ): number => x, 0.0, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, '10', x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, true, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, false, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, null, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, undefined, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, [], x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, {}, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, ( x: number ): number => x, x, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, 10, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, '10', 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, true, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, false, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, null, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, undefined, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, [ '1' ], 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, {}, 1, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, ( x: number ): number => x, 1, 0, 0.0, x, 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 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, '10', 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, true, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, false, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, null, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, undefined, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, [], 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, {}, 0, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, ( x: number ): number => x, 0, 0.0, x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, '10', 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, true, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, false, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, null, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, undefined, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, [], 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, {}, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, ( x: number ): number => x, 0.0, 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 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, '10', x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, true, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, false, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, null, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, undefined, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, [], x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, {}, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, 10, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, '10', 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, true, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, false, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, null, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, undefined, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, [ '1' ], 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, {}, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, '10', 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, true, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, false, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, null, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, undefined, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, [], 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, {}, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a tenth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, '10' ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, true ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, false ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, null ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, undefined ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, [] ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, {} ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 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 );
+
+ covarmtk.ndarray(); // $ExpectError
+ covarmtk.ndarray( x.length ); // $ExpectError
+ covarmtk.ndarray( x.length, 1 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1 ); // $ExpectError
+ covarmtk.ndarray( x.length, 1, 0.0, x, 1, 0, 0.0, x, 1, 0, 0 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/examples/index.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/examples/index.js
new file mode 100644
index 000000000000..286778b70066
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/examples/index.js
@@ -0,0 +1,34 @@
+/**
+* @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 covarmtk = require( './../lib' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+var x = discreteUniform( 10, -50, 50, opts );
+console.log( x );
+
+var y = discreteUniform( 10, -50, 50, opts );
+console.log( y );
+
+var v = covarmtk( x.length, 1, 0.0, x, 1, 0.0, y, 1 );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/accessors.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/accessors.js
new file mode 100644
index 000000000000..036076196a51
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/accessors.js
@@ -0,0 +1,86 @@
+/**
+* @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';
+
+// MAIN //
+
+/**
+* Computes the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
+*
+* @private
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {number} meanx - mean of `x`
+* @param {Object} x - first input array object
+* @param {Collection} x.data - first input array data
+* @param {Array} x.accessors - array element accessors
+* @param {integer} strideX - stride length of `x`
+* @param {NonNegativeInteger} offsetX - starting index of `x`
+* @param {number} meany - mean of `y`
+* @param {Object} y - second input array object
+* @param {Collection} y.data - second input array data
+* @param {Array} y.accessors - array element accessors
+* @param {integer} strideY - stride length of `y`
+* @param {NonNegativeInteger} offsetY - starting index of `y`
+* @returns {number} covariance
+*
+* @example
+* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+* var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+*
+* var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var v = covarmtk( 4, 1, 1.25, arraylike2object( x ), 2, 1, 1.25, arraylike2object( x ), 2, 1 );
+* // returns 6.25
+*/
+function covarmtk( N, correction, meanx, x, strideX, offsetX, meany, y, strideY, offsetY ) { // eslint-disable-line max-len
+ var xbuf;
+ var ybuf;
+ var xget;
+ var yget;
+ var ix;
+ var iy;
+ var C;
+ var n;
+ var i;
+
+ // Cache references to array data:
+ xbuf = x.data;
+ ybuf = y.data;
+
+ // Cache references to element accessors:
+ xget = x.accessors[ 0 ];
+ yget = y.accessors[ 0 ];
+
+ n = N - correction;
+ ix = offsetX;
+ iy = offsetY;
+ C = 0.0;
+ for ( i = 0; i < N; i++ ) {
+ C += ( xget( xbuf, ix ) - meanx ) * ( yget( ybuf, iy ) - meany );
+ ix += strideX;
+ iy += strideY;
+ }
+ return C / n;
+}
+
+
+// EXPORTS //
+
+module.exports = covarmtk;
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/index.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/index.js
new file mode 100644
index 000000000000..dbece1b6e4bb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/index.js
@@ -0,0 +1,59 @@
+/**
+* @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 covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
+*
+* @module @stdlib/stats/strided/covarmtk
+*
+* @example
+* var covarmtk = require( '@stdlib/stats/strided/covarmtk' );
+*
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = covarmtk( x.length, 1, 1.0/3.0, x, 1, 1.0/3.0, x, 1 );
+* // returns ~4.3333
+*
+* @example
+* var covarmtk = require( '@stdlib/stats/strided/covarmtk' );
+*
+* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
+*
+* var v = covarmtk.ndarray( 4, 1, 1.25, x, 2, 1, 1.25, x, 2, 1 );
+* // returns 6.25
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "ndarray": "main.ndarray" }
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/main.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/main.js
new file mode 100644
index 000000000000..9a2ec42f3c87
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/main.js
@@ -0,0 +1,55 @@
+/**
+* @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 stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+/**
+* Computes the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {number} meanx - mean of `x`
+* @param {NumericArray} x - first input array
+* @param {integer} strideX - stride length of `x`
+* @param {number} meany - mean of `y`
+* @param {NumericArray} y - second input array
+* @param {integer} strideY - stride length of `y`
+* @returns {number} covariance
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = covarmtk( x.length, 1, 1.0/3.0, x, 1, 1.0/3.0, x, 1 );
+* // returns ~4.3333
+*/
+function covarmtk( N, correction, meanx, x, strideX, meany, y, strideY ) {
+ return ndarray( N, correction, meanx, x, strideX, stride2offset( N, strideX ), meany, y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = covarmtk;
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/ndarray.js
new file mode 100644
index 000000000000..9340ac5d618a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/lib/ndarray.js
@@ -0,0 +1,82 @@
+/**
+* @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 arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+var accessors = require( './accessors.js' );
+
+
+// MAIN //
+
+/**
+* Computes the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {number} meanx - mean of `x`
+* @param {NumericArray} x - first input array
+* @param {integer} strideX - stride length of `x`
+* @param {NonNegativeInteger} offsetX - starting index of `x`
+* @param {number} meany - mean of `y`
+* @param {NumericArray} y - second input array
+* @param {integer} strideY - stride length of `y`
+* @param {NonNegativeInteger} offsetY - starting index of `y`
+* @returns {number} covariance
+*
+* @example
+* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
+*
+* var v = covarmtk( 4, 1, 1.25, x, 2, 1, 1.25, x, 2, 1 );
+* // returns 6.25
+*/
+function covarmtk( N, correction, meanx, x, strideX, offsetX, meany, y, strideY, offsetY ) { // eslint-disable-line max-len
+ var ox;
+ var oy;
+ var ix;
+ var iy;
+ var C;
+ var n;
+ var i;
+
+ n = N - correction;
+ if ( N <= 0 || n <= 0.0 ) {
+ return NaN;
+ }
+ ox = arraylike2object( x );
+ oy = arraylike2object( y );
+ if ( ox.accessorProtocol || oy.accessorProtocol ) {
+ return accessors( N, correction, meanx, ox, strideX, offsetX, meany, oy, strideY, offsetY ); // eslint-disable-line max-len
+ }
+ ix = offsetX;
+ iy = offsetY;
+ C = 0.0;
+ for ( i = 0; i < N; i++ ) {
+ C += ( x[ ix ] - meanx ) * ( y[ iy ] - meany );
+ ix += strideX;
+ iy += strideY;
+ }
+ return C / n;
+}
+
+
+// EXPORTS //
+
+module.exports = covarmtk;
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/package.json b/lib/node_modules/@stdlib/stats/strided/covarmtk/package.json
new file mode 100644
index 000000000000..f36867a4635b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/package.json
@@ -0,0 +1,70 @@
+{
+ "name": "@stdlib/stats/strided/covarmtk",
+ "version": "0.0.0",
+ "description": "Calculate the covariance of two strided arrays provided known means and using a one-pass textbook 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",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "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",
+ "covariance",
+ "covar",
+ "sample covariance",
+ "unbiased",
+ "correlation",
+ "variance",
+ "strided",
+ "strided array",
+ "typed",
+ "array"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.js
new file mode 100644
index 000000000000..1bfc232de244
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.js
@@ -0,0 +1,38 @@
+/**
+* @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 tape = require( 'tape' );
+var covarmtk = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof covarmtk, '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 covarmtk.ndarray, 'function', 'method is a function' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.main.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.main.js
new file mode 100644
index 000000000000..6060a51104dd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.main.js
@@ -0,0 +1,397 @@
+/**
+* @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 tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var covarmtk = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof covarmtk, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 8', function test( t ) {
+ t.strictEqual( covarmtk.length, 8, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the population covariance', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ y = [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ];
+ v = covarmtk( x.length, 0, 0.5, x, 1, 0.5, y, 1 );
+ t.strictEqual( v, -45.5/x.length, 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = covarmtk( x.length, 0, -4.0, x, 1, -4.0, x, 1 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = covarmtk( x.length, 0, 4.0, x, 1, 4.0, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the population covariance (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+ y = toAccessorArray( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] );
+ v = covarmtk( x.length, 0, 0.5, x, 1, 0.5, y, 1 );
+ t.strictEqual( v, -45.5/x.length, 'returns expected value' );
+
+ x = toAccessorArray( [ -4.0, -4.0 ] );
+ v = covarmtk( x.length, 0, -4.0, x, 1, -4.0, x, 1 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = toAccessorArray( [ NaN, 4.0 ] );
+ v = covarmtk( x.length, 0, 4.0, x, 1, 4.0, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample covariance', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ y = [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ];
+ v = covarmtk( x.length, 1, 0.5, x, 1, 0.5, y, 1 );
+ t.strictEqual( v, -45.5/(x.length-1), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = covarmtk( x.length, 1, -4.0, x, 1, -4.0, x, 1 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = covarmtk( x.length, 1, 4.0, x, 1, 4.0, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample covariance (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+ y = toAccessorArray( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] );
+ v = covarmtk( x.length, 1, 0.5, x, 1, 0.5, y, 1 );
+ t.strictEqual( v, -45.5/(x.length-1), 'returns expected value' );
+
+ x = toAccessorArray( [ -4.0, -4.0 ] );
+ v = covarmtk( x.length, 1, -4.0, x, 1, -4.0, x, 1 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = toAccessorArray( [ NaN, 4.0 ] );
+ v = covarmtk( x.length, 1, 4.0, x, 1, 4.0, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+ v = covarmtk( 0, 1, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( -1, 1, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+ v = covarmtk( 0, 1, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( -1, 1, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+ v = covarmtk( x.length, x.length, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( x.length, x.length+1, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+ v = covarmtk( x.length, x.length, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( x.length, x.length+1, 0.6, x, 1, 0.6, x, 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports stride parameters', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ];
+
+ y = [
+ 2.0, // 0
+ 2.0,
+ 1.0, // 1
+ -7.0,
+ 4.0, // 2
+ 3.0,
+ -2.0, // 3
+ 2.0
+ ];
+
+ v = covarmtk( 4, 1, 1.25, x, 2, 1.25, y, 2 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports stride parameters (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+
+ y = toAccessorArray([
+ 2.0, // 0
+ 2.0,
+ 1.0, // 1
+ -7.0,
+ 4.0, // 2
+ 3.0,
+ -2.0, // 3
+ 2.0
+ ]);
+
+ v = covarmtk( 4, 1, 1.25, x, 2, 1.25, y, 2 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative stride parameters', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ];
+
+ y = [
+ 2.0, // 3
+ 2.0,
+ 1.0, // 2
+ -7.0,
+ 4.0, // 1
+ 3.0,
+ -2.0, // 0
+ 2.0
+ ];
+
+ v = covarmtk( 4, 1, 1.25, x, -2, 1.25, y, -2 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative stride parameters (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+
+ y = toAccessorArray([
+ 2.0, // 3
+ 2.0,
+ 1.0, // 2
+ -7.0,
+ 4.0, // 1
+ 3.0,
+ -2.0, // 0
+ 2.0
+ ]);
+
+ v = covarmtk( 4, 1, 1.25, x, -2, 1.25, y, -2 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports view offsets', function test( t ) {
+ var x0;
+ var x1;
+ var y0;
+ var y1;
+ 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
+ ]);
+
+ y0 = new Float64Array([
+ 2.0,
+ -2.0, // 0
+ 2.0,
+ 1.0, // 1
+ -2.0,
+ 4.0, // 2
+ 3.0,
+ 2.0, // 3
+ 6.0
+ ]);
+
+ x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+ y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+ v = covarmtk( 4, 1, 1.25, x1, 2, 1.25, y1, 2 );
+ t.strictEqual( v, 5.75/3, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports view offsets (accessors)', function test( t ) {
+ var x0;
+ var x1;
+ var y0;
+ var y1;
+ 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
+ ]);
+
+ y0 = new Float64Array([
+ 2.0,
+ -2.0, // 0
+ 2.0,
+ 1.0, // 1
+ -2.0,
+ 4.0, // 2
+ 3.0,
+ 2.0, // 3
+ 6.0
+ ]);
+
+ x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+ y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+ v = covarmtk( 4, 1, 1.25, toAccessorArray( x1 ), 2, 1.25, toAccessorArray( y1 ), 2 );
+ t.strictEqual( v, 5.75/3, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.ndarray.js
new file mode 100644
index 000000000000..2a39b6ca83a7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/covarmtk/test/test.ndarray.js
@@ -0,0 +1,382 @@
+/**
+* @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 tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var covarmtk = require( './../lib/ndarray.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof covarmtk, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 10', function test( t ) {
+ t.strictEqual( covarmtk.length, 10, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the population covariance', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ y = [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ];
+ v = covarmtk( x.length, 0, 0.5, x, 1, 0, 0.5, y, 1, 0 );
+ t.strictEqual( v, -45.5/x.length, 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = covarmtk( x.length, 0, -4.0, x, 1, 0, -4.0, x, 1, 0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = covarmtk( x.length, 0, 4.0, x, 1, 0, 4.0, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the population covariance (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+ y = toAccessorArray( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] );
+ v = covarmtk( x.length, 0, 0.5, x, 1, 0, 0.5, y, 1, 0 );
+ t.strictEqual( v, -45.5/x.length, 'returns expected value' );
+
+ x = toAccessorArray( [ -4.0, -4.0 ] );
+ v = covarmtk( x.length, 0, -4.0, x, 1, 0, -4.0, x, 1, 0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = toAccessorArray( [ NaN, 4.0 ] );
+ v = covarmtk( x.length, 0, 4.0, x, 1, 0, 4.0, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample covariance', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ y = [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ];
+ v = covarmtk( x.length, 1, 0.5, x, 1, 0, 0.5, y, 1, 0 );
+ t.strictEqual( v, -45.5/(x.length-1), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = covarmtk( x.length, 1, -4.0, x, 1, 0, -4.0, x, 1, 0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = covarmtk( x.length, 1, 4.0, x, 1, 0, 4.0, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample covariance (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+ y = toAccessorArray( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] );
+ v = covarmtk( x.length, 1, 0.5, x, 1, 0, 0.5, y, 1, 0 );
+ t.strictEqual( v, -45.5/(x.length-1), 'returns expected value' );
+
+ x = toAccessorArray( [ -4.0, -4.0 ] );
+ v = covarmtk( x.length, 1, -4.0, x, 1, 0, -4.0, x, 1, 0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = toAccessorArray( [ NaN, 4.0 ] );
+ v = covarmtk( x.length, 1, 4.0, x, 1, 0, 4.0, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+ v = covarmtk( 0, 1, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( -1, 1, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+ v = covarmtk( 0, 1, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( -1, 1, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
+
+ v = covarmtk( x.length, x.length, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( x.length, x.length+1, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+ v = covarmtk( x.length, x.length, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = covarmtk( x.length, x.length+1, 0.6, x, 1, 0, 0.6, x, 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports stride parameters', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ];
+
+ y = [
+ 2.0, // 0
+ 2.0,
+ 1.0, // 1
+ -7.0,
+ 4.0, // 2
+ 3.0,
+ -2.0, // 3
+ 2.0
+ ];
+
+ v = covarmtk( 4, 1, 1.25, x, 2, 0, 1.25, y, 2, 0 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports stride parameters (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+
+ y = toAccessorArray([
+ 2.0, // 0
+ 2.0,
+ 1.0, // 1
+ -7.0,
+ 4.0, // 2
+ 3.0,
+ -2.0, // 3
+ 2.0
+ ]);
+
+ v = covarmtk( 4, 1, 1.25, x, 2, 0, 1.25, y, 2, 0 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative stride parameters', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ];
+
+ y = [
+ 2.0, // 3
+ 2.0,
+ 1.0, // 2
+ -7.0,
+ 4.0, // 1
+ 3.0,
+ -2.0, // 0
+ 2.0
+ ];
+
+ v = covarmtk( 4, 1, 1.25, x, -2, 6, 1.25, y, -2, 6 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative stride parameters (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+
+ y = toAccessorArray([
+ 2.0, // 3
+ 2.0,
+ 1.0, // 2
+ -7.0,
+ 4.0, // 1
+ 3.0,
+ -2.0, // 0
+ 2.0
+ ]);
+
+ v = covarmtk( 4, 1, 1.25, x, -2, 6, 1.25, y, -2, 6 );
+
+ t.strictEqual( v, -18.25/3, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports offset parameters', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = [
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ];
+
+ y = [
+ 2.0,
+ 4.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 1.0, // 2
+ 3.0,
+ 2.0 // 3
+ ];
+
+ v = covarmtk( 4, 1, 1.25, x, 2, 1, 1.25, y, 2, 1 );
+ t.strictEqual( v, 11.75/3, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports offset parameters (accessors)', function test( t ) {
+ var x;
+ var y;
+ var v;
+
+ x = toAccessorArray([
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ]);
+
+ y = toAccessorArray([
+ 2.0,
+ 4.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 1.0, // 2
+ 3.0,
+ 2.0 // 3
+ ]);
+
+ v = covarmtk( 4, 1, 1.25, x, 2, 1, 1.25, y, 2, 1 );
+ t.strictEqual( v, 11.75/3, 'returns expected value' );
+
+ t.end();
+});