diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/README.md b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/README.md
new file mode 100644
index 000000000000..66c1ec851e1a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/README.md
@@ -0,0 +1,214 @@
+
+
+# incrnanmeanvar
+
+> Compute an [arithmetic mean][arithmetic-mean] and an [unbiased sample variance][sample-variance] incrementally, ignoring `NaN` values.
+
+
+
+The [arithmetic mean][arithmetic-mean] is defined as
+
+
+
+```math
+\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i
+```
+
+
+
+
+
+and the [unbiased sample variance][sample-variance] is defined as
+
+
+
+```math
+s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2
+```
+
+
+
+
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' );
+```
+
+#### incrnanmeanvar( \[out] )
+
+Returns an accumulator `function` which incrementally computes an [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance], ignoring `NaN` values.
+
+```javascript
+var accumulator = incrnanmeanvar();
+```
+
+By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var accumulator = incrnanmeanvar( new Float64Array( 2 ) );
+```
+
+#### accumulator( \[x] )
+
+If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values.
+
+```javascript
+var accumulator = incrnanmeanvar();
+
+var mv = accumulator();
+// returns null
+
+mv = accumulator( 2.0 );
+// returns [ 2.0, 0.0 ]
+
+mv = accumulator( 1.0 );
+// returns [ 1.5, 0.5 ]
+
+mv = accumulator( 3.0 );
+// returns [ 2.0, 1.0 ]
+
+mv = accumulator( NaN );
+// returns [ 2.0, 1.0 ]
+
+mv = accumulator( -7.0 );
+// returns [ -0.25, ~20.92 ]
+
+mv = accumulator( -5.0 );
+// returns [ -1.2, 20.2 ]
+
+mv = accumulator();
+// returns [ -1.2, 20.2 ]
+```
+
+
+
+
+
+
+
+## Notes
+
+- Input values are type checked; if a NaN value is provided, the accumulator skips the update and continues to return the previous state. If non-numeric inputs are possible, you are advised to type check and handle them accordingly **before** passing the value to the accumulator function.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ArrayBuffer = require( '@stdlib/array/buffer' );
+var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' );
+
+var offset;
+var acc;
+var buf;
+var out;
+var mv;
+var N;
+var v;
+var i;
+var j;
+
+// Define the number of accumulators:
+N = 5;
+
+// Create an array buffer for storing accumulator output:
+buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element
+
+// Initialize accumulators:
+acc = [];
+for ( i = 0; i < N; i++ ) {
+ // Compute the byte offset:
+ offset = i * 2 * 8; // stride=2, bytes_per_element=8
+
+ // Create a new view for storing accumulated values:
+ out = new Float64Array( buf, offset, 2 );
+
+ // Initialize an accumulator which will write results to the view:
+ acc.push( incrnanmeanvar( out ) );
+}
+
+// Simulate data and update the sample means and variances...
+for ( i = 0; i < 100; i++ ) {
+ for ( j = 0; j < N; j++ ) {
+ if ( randu() < 0.2 ) {
+ v = NaN;
+ } else {
+ v = randu() * 100.0 * (j+1);
+ }
+ acc[ j ]( v );
+ }
+}
+
+// Print the final results:
+console.log( 'Mean\tVariance' );
+for ( i = 0; i < N; i++ ) {
+ mv = acc[ i ]();
+ console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) );
+}
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[sample-variance]: https://en.wikipedia.org/wiki/Variance
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/benchmark/benchmark.js
new file mode 100644
index 000000000000..fb58216a6107
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/benchmark/benchmark.js
@@ -0,0 +1,70 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var randu = require( '@stdlib/random/base/randu' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var incrnanmeanvar = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var f;
+ var i;
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ f = incrnanmeanvar();
+ if ( typeof f !== 'function' ) {
+ b.fail( 'should return a function' );
+ }
+ }
+ b.toc();
+ if ( typeof f !== 'function' ) {
+ b.fail( 'should return a function' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( format( '%s::accumulator', pkg ), function benchmark( b ) {
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanmeanvar();
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = acc( randu() );
+ if ( v.length !== 2 ) {
+ b.fail( 'should contain two elements' );
+ }
+ }
+ b.toc();
+ if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_arithmetic_mean.svg
new file mode 100644
index 000000000000..aea7a5f6687a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_arithmetic_mean.svg
@@ -0,0 +1,43 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_unbiased_sample_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_unbiased_sample_variance.svg
new file mode 100644
index 000000000000..1ae1283e7fb1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_unbiased_sample_variance.svg
@@ -0,0 +1,61 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/repl.txt
new file mode 100644
index 000000000000..1862fbb8518d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/repl.txt
@@ -0,0 +1,43 @@
+
+{{alias}}( [out] )
+ Returns an accumulator function which incrementally computes an arithmetic
+ mean and unbiased sample variance, ignoring `NaN` values.
+
+ If provided a value, the accumulator function returns updated accumulated
+ values. If not provided a value, the accumulator function returns the
+ current accumulated values.
+
+ If provided `NaN`, the update is skipped and the accumulator continues to
+ return the previous accumulated values.
+
+ Parameters
+ ----------
+ out: Array|TypedArray (optional)
+ Output array.
+
+ Returns
+ -------
+ acc: Function
+ Accumulator function.
+
+ Examples
+ --------
+ > var accumulator = {{alias}}();
+ > var mv = accumulator()
+ null
+ > mv = accumulator( 2.0 )
+ [ 2.0, 0.0 ]
+ > mv = accumulator( -5.0 )
+ [ -1.5, 24.5 ]
+ > mv = accumulator( 3.0 )
+ [ 0.0, 19.0 ]
+ > mv = accumulator( NaN )
+ [ 0.0, 19.0 ]
+ > mv = accumulator( 5.0 )
+ [ 1.25, ~18.92 ]
+ > mv = accumulator()
+ [ 1.25, ~18.92 ]
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/index.d.ts
new file mode 100644
index 000000000000..541dd125700c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/index.d.ts
@@ -0,0 +1,72 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+import { ArrayLike } from '@stdlib/types/array';
+
+/**
+* If provided a value, the accumulator function returns updated results. If not provided a value, the accumulator function returns the current results.
+*
+* ## Notes
+*
+* - If provided `NaN`, the value is ignored and the accumulator function returns the current accumulated values.
+*
+* @param x - input value
+* @returns output array or null
+*/
+type accumulator = ( x?: number ) => ArrayLike | null;
+
+/**
+* Returns an accumulator function which incrementally computes an arithmetic mean and unbiased sample variance, ignoring `NaN` values.
+*
+* @param out - output array
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanmeanvar();
+*
+* var mv = accumulator();
+* // returns null
+*
+* mv = accumulator( 2.0 );
+* // returns [ 2.0, 0.0 ]
+*
+* mv = accumulator( -5.0 );
+* // returns [ -1.5, 24.5 ]
+*
+* mv = accumulator( 3.0 );
+* // returns [ 0.0, 19.0 ]
+*
+* mv = accumulator( NaN );
+* // returns [ 0.0, 19.0 ]
+*
+* mv = accumulator( 5.0 );
+* // returns [ 1.25, ~18.92 ]
+*
+* mv = accumulator();
+* // returns [ 1.25, ~18.92 ]
+*/
+declare function incrnanmeanvar( out?: ArrayLike ): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanmeanvar;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/test.ts
new file mode 100644
index 000000000000..4b6565bbc5da
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/test.ts
@@ -0,0 +1,61 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import incrnanmeanvar = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+ incrnanmeanvar(); // $ExpectType accumulator
+ const out = [ 0.0, 0.0 ];
+ incrnanmeanvar( out ); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided an argument that is not an array-like object of numbers...
+{
+ incrnanmeanvar( '5' ); // $ExpectError
+ incrnanmeanvar( 5 ); // $ExpectError
+ incrnanmeanvar( true ); // $ExpectError
+ incrnanmeanvar( false ); // $ExpectError
+ incrnanmeanvar( null ); // $ExpectError
+ incrnanmeanvar( {} ); // $ExpectError
+ incrnanmeanvar( ( x: number ): number => x ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+ const acc = incrnanmeanvar();
+
+ acc(); // $ExpectType ArrayLike | null
+ acc( 3.14 ); // $ExpectType ArrayLike | null
+}
+
+// The compiler throws an error if the returned accumulator function is provided invalid arguments...
+{
+ const acc = incrnanmeanvar();
+
+ acc( '5' ); // $ExpectError
+ acc( true ); // $ExpectError
+ acc( false ); // $ExpectError
+ acc( null ); // $ExpectError
+ acc( [] ); // $ExpectError
+ acc( {} ); // $ExpectError
+ acc( ( x: number ): number => x ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/examples/index.js
new file mode 100644
index 000000000000..99ec426463e2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/examples/index.js
@@ -0,0 +1,72 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var randu = require( '@stdlib/random/base/randu' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ArrayBuffer = require( '@stdlib/array/buffer' );
+var incrnanmeanvar = require( './../lib' );
+
+var offset;
+var acc;
+var buf;
+var out;
+var mv;
+var N;
+var v;
+var i;
+var j;
+
+// Define the number of accumulators:
+N = 5;
+
+// Create an array buffer for storing accumulator output:
+buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element
+
+// Initialize accumulators:
+acc = [];
+for ( i = 0; i < N; i++ ) {
+ // Compute the byte offset:
+ offset = i * 2 * 8; // stride=2, bytes_per_element=8
+
+ // Create a new view for storing accumulated values:
+ out = new Float64Array( buf, offset, 2 );
+
+ // Initialize an accumulator which will write results to the view:
+ acc.push( incrnanmeanvar( out ) );
+}
+
+// Simulate data and update the sample means and variances...
+for ( i = 0; i < 100; i++ ) {
+ for ( j = 0; j < N; j++ ) {
+ if ( randu() < 0.2 ) {
+ v = NaN;
+ } else {
+ v = randu() * 100.0 * (j+1);
+ }
+ acc[ j ]( v );
+ }
+}
+
+// Print the final results:
+console.log( 'Mean\tVariance' );
+for ( i = 0; i < N; i++ ) {
+ mv = acc[ i ]();
+ console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/index.js
new file mode 100644
index 000000000000..6c8b4e3d3f81
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/index.js
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute an arithmetic mean and unbiased sample variance incrementally, ignoring `NaN` values.
+*
+* @module @stdlib/stats/incr/nanmeanvar
+*
+* @example
+* var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' );
+*
+* var accumulator = incrnanmeanvar();
+*
+* var mv = accumulator();
+* // returns null
+*
+* mv = accumulator( 2.0 );
+* // returns [ 2.0, 0.0 ]
+*
+* mv = accumulator( -5.0 );
+* // returns [ -1.5, 24.5 ]
+*
+* mv = accumulator( 3.0 );
+* // returns [ 0.0, 19.0 ]
+*
+* mv = accumulator( NaN );
+* // returns [ 0.0, 19.0 ]
+*
+* mv = accumulator( 5.0 );
+* // returns [ 1.25, ~18.92 ]
+*
+* mv = accumulator();
+* // returns [ 1.25, ~18.92 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/main.js
new file mode 100644
index 000000000000..6e566e6a3d09
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/main.js
@@ -0,0 +1,93 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
+var incrmeanvar = require( '@stdlib/stats/incr/meanvar' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes an arithmetic mean and unbiased sample variance, ignoring `NaN` values.
+*
+* ## References
+*
+* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022).
+* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961).
+*
+* @param {Collection} [out] - output array
+* @throws {TypeError} output argument must be array-like
+* @returns {Function} accumulator function
+*
+* @example
+* var accumulator = incrnanmeanvar();
+*
+* var mv = accumulator();
+* // returns null
+*
+* mv = accumulator( 2.0 );
+* // returns [ 2.0, 0.0 ]
+*
+* mv = accumulator( -5.0 );
+* // returns [ -1.5, 24.5 ]
+*
+* mv = accumulator( 3.0 );
+* // returns [ 0.0, 19.0 ]
+*
+* mv = accumulator( NaN );
+* // returns [ 0.0, 19.0 ]
+*
+* mv = accumulator( 5.0 );
+* // returns [ 1.25, ~18.92 ]
+*
+* mv = accumulator();
+* // returns [ 1.25, ~18.92 ]
+*/
+function incrnanmeanvar( out ) {
+ var meanvar;
+ if ( arguments.length > 0 ) {
+ meanvar = incrmeanvar( out );
+ } else {
+ meanvar = incrmeanvar();
+ }
+ return accumulator;
+
+ /**
+ * If provided a value, the accumulator function returns updated results. If not provided a value, the accumulator function returns the current results.
+ *
+ * @private
+ * @param {number} [x] - input value
+ * @returns {(ArrayLikeObject|null)} output array or null
+ */
+ function accumulator( x ) {
+ if ( arguments.length === 0 || isnan( x ) || !isNumber( x ) ) {
+ return meanvar();
+ }
+ return meanvar( x );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanmeanvar;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/package.json b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/package.json
new file mode 100644
index 000000000000..ec64e00b032c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/package.json
@@ -0,0 +1,73 @@
+{
+ "name": "@stdlib/stats/incr/nanmeanvar",
+ "version": "0.0.0",
+ "description": "Compute an arithmetic mean and unbiased sample variance incrementally, ignoring `NaN` values.",
+ "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",
+ "average",
+ "avg",
+ "mean",
+ "arithmetic mean",
+ "variance",
+ "sample variance",
+ "unbiased",
+ "var",
+ "dispersion",
+ "standard deviation",
+ "stdev",
+ "central tendency",
+ "incremental",
+ "accumulator"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/test/test.js
new file mode 100644
index 000000000000..5f2a526e7bf9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/test/test.js
@@ -0,0 +1,203 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var incrnanmeanvar = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof incrnanmeanvar, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ -5.0,
+ true,
+ false,
+ null,
+ void 0,
+ NaN,
+ {},
+ function noop() {}
+ ];
+
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ incrnanmeanvar( value );
+ };
+ }
+});
+
+tape( 'the function returns an accumulator function', function test( t ) {
+ t.equal( typeof incrnanmeanvar(), 'function', 'returns a function' );
+ t.end();
+});
+
+tape( 'the function returns an accumulator function (output)', function test( t ) {
+ t.equal( typeof incrnanmeanvar( [ 0.0, 0.0 ] ), 'function', 'returns a function' );
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes an arithmetic mean and unbiased sample variance', function test( t ) {
+ var expected;
+ var actual;
+ var data;
+ var acc;
+ var N;
+ var i;
+
+ data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0 ];
+ N = data.length;
+
+ // Test against Julia:
+ expected = [
+ [ 2.0, 0.0 ],
+ [ 2.0, 0.0 ],
+ [ 2.5, 0.5 ],
+ [ 7.0/3.0, 0.33333333333333337 ],
+ [ 7.0/3.0, 0.33333333333333337 ],
+ [ 11.0/4.0, 0.9166666666666666 ],
+ [ 14.0/5.0, 0.7 ],
+ [ 18.0/6.0, 0.8 ]
+ ];
+
+ acc = incrnanmeanvar();
+
+ for ( i = 0; i < N; i++ ) {
+ actual = acc( data[ i ] );
+ t.deepEqual( actual, expected[ i ], 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes an arithmetic mean and unbiased sample variance (output)', function test( t ) {
+ var expected;
+ var actual;
+ var data;
+ var acc;
+ var out;
+ var N;
+ var i;
+
+ data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0 ];
+ N = data.length;
+
+ // Test against Julia:
+ expected = [
+ [ 2.0, 0.0 ],
+ [ 2.0, 0.0 ],
+ [ 2.5, 0.5 ],
+ [ 7.0/3.0, 0.33333333333333337 ],
+ [ 7.0/3.0, 0.33333333333333337 ],
+ [ 11.0/4.0, 0.9166666666666666 ],
+ [ 14.0/5.0, 0.7 ],
+ [ 18.0/6.0, 0.8 ]
+ ];
+ out = [ 0.0, 0.0 ];
+ acc = incrnanmeanvar( out );
+
+ for ( i = 0; i < N; i++ ) {
+ actual = acc( data[ i ] );
+ t.equal( actual, out, 'returns output array' );
+ t.deepEqual( actual, expected[ i ], 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current mean and unbiased sample variance', function test( t ) {
+ var data;
+ var acc;
+ var i;
+
+ data = [ 2.0, 3.0, NaN, 1.0 ];
+ acc = incrnanmeanvar();
+ for ( i = 0; i < data.length; i++ ) {
+ acc( data[ i ] );
+ }
+ t.deepEqual( acc(), [ 2.0, 1.0 ], 'returns expected value' );
+ t.end();
+});
+
+tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) {
+ var acc = incrnanmeanvar();
+ t.equal( acc(), null, 'returns null' );
+ t.equal( acc(), null, 'returns null' );
+ t.equal( acc(), null, 'returns null' );
+ t.end();
+});
+
+tape( 'the sample variance is `0` until at least 2 datums have been provided', function test( t ) {
+ var acc;
+ var mv;
+
+ acc = incrnanmeanvar();
+
+ mv = acc();
+ t.equal( mv, null, 'returns null' );
+
+ mv = acc( 3.0 );
+ t.equal( mv[ 1 ], 0.0, 'returns expected value' );
+
+ mv = acc();
+ t.equal( mv[ 1 ], 0.0, 'returns expected value' );
+
+ mv = acc( 5.0 );
+ t.notEqual( mv[ 1 ], 0.0, 'does not return 0' );
+
+ mv = acc();
+ t.notEqual( mv[ 1 ], 0.0, 'does not return 0' );
+
+ t.end();
+});
+
+tape( 'if the first value is NaN, the accumulator returns its initial state', function test( t ) {
+ var state;
+ var acc;
+
+ acc = incrnanmeanvar();
+
+ // First update is NaN, so no valid update occurs:
+ state = acc( NaN );
+ t.equal( state, null, 'returns null for initial state when first input is NaN' );
+
+ // Subsequent call without an update should still return null:
+ state = acc();
+ t.equal( state, null, 'remains at initial state (null) when no valid update is provided' );
+
+ // Now provide a valid update to see the state change:
+ state = acc( 2.0 );
+ t.deepEqual( state, [ 2.0, 0.0 ], 'updates state correctly after a valid input following an initial NaN' );
+ t.end();
+});