diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/README.md b/lib/node_modules/@stdlib/stats/incr/nanewvariance/README.md
new file mode 100644
index 000000000000..c65abc49c7c3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/README.md
@@ -0,0 +1,148 @@
+
+
+# incrnanewvariance
+
+> Compute an [exponentially weighted variance][exponentially weighted variance] incrementally, ignoring `NaN` values.
+
+
+
+The [exponentially weighted variance][exponentially weighted variance] is defined as
+
+
+
+```math
+S_n = \begin{cases} 0 & \textrm{if}\ n = 0 \\ (1 - \alpha) (S_{n-1} + \alpha(x_n - \mu_{n-1})^2) & \textrm{if}\ n > 0 \end{cases}
+```
+
+
+
+
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' );
+```
+
+#### incrnanewvariance( alpha )
+
+Returns an accumulator function which incrementally computes an [exponentially weighted variance][exponentially weighted variance], ignoring `NaN` values.
+
+```javascript
+var accumulator = incrnanewvariance( 0.5 );
+```
+
+#### accumulator( \[x] )
+
+If provided an input value `x`, the accumulator function returns an updated exponentially weighted variance. If not provided an input value `x`, the accumulator function returns the current exponentially weighted variance.
+
+```javascript
+var accumulator = incrnanewvariance( 0.5 );
+
+var v = accumulator();
+// returns null
+
+v = accumulator( 2.0 );
+// returns 0
+
+v = accumulator( 4.0 );
+// returns 1
+
+v = accumulator( NaN );
+// returns 1
+
+v = accumulator( 5.0 );
+// returns 1.5
+
+v = accumulator();
+// returns 1.5
+```
+
+
+
+
+
+
+
+## Notes
+
+- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' );
+
+var accumulator;
+var v;
+var i;
+
+// Initialize an accumulator with smoothing factor α = 0.5:
+accumulator = incrnanewvariance( 0.5 );
+
+// For each simulated datum, update the exponentially weighted variance...
+for ( i = 0; i < 100; i++ ) {
+ // With a 20% chance, provide NaN to test that invalid inputs are ignored:
+ v = ( randu() < 0.2 ) ? NaN : randu() * 100.0;
+ accumulator( v );
+}
+console.log( accumulator() );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[exponentially weighted variance]: https://en.wikipedia.org/wiki/EWMA_chart
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/benchmark/benchmark.js
new file mode 100644
index 000000000000..31302d039195
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/benchmark/benchmark.js
@@ -0,0 +1,68 @@
+/**
+* @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 nanewvariance = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var f;
+ var i;
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ f = nanewvariance( 0.5 );
+ 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 = nanewvariance( 0.5 );
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = acc( randu() );
+ if ( v !== v ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( v !== v ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/img/equation_exponentially_weighted_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/img/equation_exponentially_weighted_variance.svg
new file mode 100644
index 000000000000..ec759179e837
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/img/equation_exponentially_weighted_variance.svg
@@ -0,0 +1,89 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/repl.txt
new file mode 100644
index 000000000000..8a7fe4f004c9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/repl.txt
@@ -0,0 +1,42 @@
+
+{{alias}}( α )
+ Returns an accumulator function which incrementally computes an
+ exponentially weighted variance, where α is a smoothing factor between 0 and
+ 1. This accumulator ignores any input values that are `NaN`.
+
+ If provided a value, the accumulator function returns an updated variance.
+ If not provided a value, the accumulator function returns the current
+ variance.
+
+ If provided `NaN` or a value which, when used in computations, results in
+ `NaN`, that input is ignored and the accumulated variance remains unchanged.
+
+ Parameters
+ ----------
+ α: number
+ Smoothing factor (value between 0 and 1).
+
+ Returns
+ -------
+ acc: Function
+ Accumulator function.
+
+ Examples
+ --------
+ > var accumulator = {{alias}}( 0.5 );
+ > var v = accumulator()
+ null
+ > v = accumulator( 2.0 )
+ 0
+ > v = accumulator( 4.0 )
+ 1
+ > v = accumulator( NaN )
+ 1
+ > v = accumulator( 5.0 )
+ 1.5
+ > v = accumulator()
+ 1.5
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/index.d.ts
new file mode 100644
index 000000000000..d352ce759321
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/index.d.ts
@@ -0,0 +1,69 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+/**
+* If provided a value, the accumulator function returns an updated variance. If not provided a value, the accumulator function returns the current variance.
+*
+* ## Notes
+*
+* - If provided `NaN`, the input is ignored and the accumulated value remains unchanged.
+*
+* @param x - value
+* @returns variance or null
+*/
+type accumulator = ( x?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes an exponentially weighted variance, ignoring `NaN` values.
+*
+* @param alpha - smoothing factor
+* @throws must provide a nonnegative number
+* @throws must be on the interval `[0,1]`
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanewvariance( 0.5 );
+*
+* var v = accumulator();
+* // returns null
+*
+* v = accumulator( 2.0 );
+* // returns 0
+*
+* v = accumulator( 4.0 );
+* // returns 1.0
+*
+* v = accumulator( NaN );
+* // returns 1.0
+*
+* v = accumulator( 5.0 );
+* // returns 1.5
+*
+* v = accumulator();
+* // returns 1.5
+*/
+declare function incrnanewvariance( alpha: number ): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanewvariance;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/test.ts
new file mode 100644
index 000000000000..ae83d18dc3d5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/test.ts
@@ -0,0 +1,58 @@
+/*
+* @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 nanewvariance = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+ nanewvariance( 0.5 ); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided an argument that is not a number...
+{
+ nanewvariance( '5' ); // $ExpectError
+ nanewvariance( true ); // $ExpectError
+ nanewvariance( false ); // $ExpectError
+ nanewvariance( null ); // $ExpectError
+ nanewvariance( undefined ); // $ExpectError
+ nanewvariance( [] ); // $ExpectError
+ nanewvariance( {} ); // $ExpectError
+ nanewvariance( ( x: number ): number => x ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+ const acc = nanewvariance( 0.5 );
+ acc(); // $ExpectType number | null
+ acc( 3.14 ); // $ExpectType number | null
+}
+
+// The compiler throws an error if the returned accumulator function is provided invalid arguments...
+{
+ const acc = nanewvariance( 0.5 );
+ 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/nanewvariance/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/examples/index.js
new file mode 100644
index 000000000000..e690b056e08d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var nanewvariance = require( './..' );
+
+var accumulator;
+var s2;
+var v;
+var i;
+
+// Initialize an accumulator:
+accumulator = nanewvariance( 0.5 );
+
+// For each simulated datum, update the exponentially weighted variance...
+console.log( '\nValue\tVariance\n' );
+for ( i = 0; i < 100; i++ ) {
+ v = ( randu() < 0.2 ) ? NaN : randu() * 100.0;
+ s2 = accumulator( v );
+ console.log( '%s\t%s', ( isnan( v ) ) ? 'NaN' : v.toFixed( 4 ), ( s2 === null ) ? 'null' : s2.toFixed( 4 ) );
+}
+console.log( '\nFinal variance: %s\n', ( accumulator() === null ) ? 'null' : accumulator().toFixed( 4 ) );
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/index.js
new file mode 100644
index 000000000000..2470b910ecf1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/index.js
@@ -0,0 +1,57 @@
+/**
+* @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 exponentially weighted variance incrementally, ignoring `NaN` values.
+*
+* @module @stdlib/stats/incr/nanewvariance
+*
+* @example
+* var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' );
+*
+* var accumulator = incrnanewvariance( 0.5 );
+*
+* var v = accumulator();
+* // returns null
+*
+* v = accumulator( 2.0 );
+* // returns 0
+*
+* v = accumulator( 4.0 );
+* // returns 1.0
+*
+* v = accumulator( NaN );
+* // returns 1.0
+*
+* v = accumulator( 5.0 );
+* // returns 1.5
+*
+* v = accumulator();
+* // returns 1.5
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/main.js
new file mode 100644
index 000000000000..8df03ffe3dfc
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/main.js
@@ -0,0 +1,83 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var increwvariance = require( '@stdlib/stats/incr/ewvariance' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes an exponentially weighted variance, ignoring `NaN` values.
+*
+* @param {NonNegativeNumber} alpha - smoothing factor
+* @throws {TypeError} must provide a nonnegative number
+* @throws {RangeError} must be on the interval `[0,1]`
+* @returns {Function} accumulator function
+*
+* @example
+* var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' );
+*
+* var accumulator = incrnanewvariance( 0.5 );
+*
+* var v = accumulator();
+* // returns null
+*
+* v = accumulator( 2.0 );
+* // returns 0
+*
+* v = accumulator( 4.0 );
+* // returns 1.0
+*
+* v = accumulator( NaN );
+* // returns 1.0
+*
+* v = accumulator( 5.0 );
+* // returns 1.5
+*
+* v = accumulator();
+* // returns 1.5
+*/
+function incrnanewvariance( alpha ) {
+ var acc = increwvariance( alpha );
+ return accumulator;
+
+ /**
+ * Updates and returns the exponentially weighted variance when provided a numeric input.
+ * If no input is provided, returns the current exponentially weighted variance.
+ *
+ * @private
+ * @param {number} [x] - new value
+ * @returns {(number|null)} updated exponentially weighted variance or null
+ */
+ function accumulator( x ) {
+ if ( arguments.length === 0 || isnan( x ) ) {
+ return acc();
+ }
+ return acc( x );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanewvariance;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/package.json b/lib/node_modules/@stdlib/stats/incr/nanewvariance/package.json
new file mode 100644
index 000000000000..fb7d368454f2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/package.json
@@ -0,0 +1,66 @@
+{
+ "name": "@stdlib/stats/incr/nanewvariance",
+ "version": "0.0.0",
+ "description": "Compute an exponentially weighted 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",
+ "weighted variance",
+ "ewvariance",
+ "variance",
+ "exponential",
+ "smoothing factor",
+ "incremental",
+ "accumulator"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/test/test.js
new file mode 100644
index 000000000000..87bb602bec78
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/test/test.js
@@ -0,0 +1,94 @@
+/**
+* @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 nanewvariance = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.end();
+});
+
+tape( 'the initial accumulated value is `null`', function test( t ) {
+ var acc = nanewvariance( 0.5 );
+ t.strictEqual( acc(), null, 'returns null initially' );
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes an exponentially weighted variance', function test( t ) {
+ var expected;
+ var actual;
+ var data;
+ var acc;
+ var i;
+
+ data = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0 ];
+ expected = [
+ 0.0, // after 1st input
+ 0.25, // after 2nd input
+ 0.1875, // after 3rd input
+ 0.859375, // after 4th input
+ 0.43359375, // after 5th input
+ 0.4365234375 // after 6th input
+ ];
+
+ actual = [];
+ acc = nanewvariance( 0.5 );
+ for ( i = 0; i < data.length; i++ ) {
+ actual.push( acc( data[ i ] ) );
+ }
+ t.deepEqual( actual, expected, 'returns expected values' );
+ t.end();
+});
+
+tape( 'if not provided an input value, accumulator returns current variance', function test( t ) {
+ var data;
+ var acc;
+ var i;
+
+ data = [ 2.0, 3.0, 1.0 ];
+ acc = nanewvariance( 0.5 );
+ for ( i = 0; i < data.length; i++ ) {
+ acc( data[ i ] );
+ }
+ t.strictEqual( acc(), 0.6875, 'returns expected variance' );
+ t.end();
+});
+
+tape( 'the accumulator function skips NaN inputs', function test( t ) {
+ var acc = nanewvariance( 0.5 );
+ var v;
+
+ v = acc( 2.0 );
+ t.strictEqual( v, 0.0, 'returns 0.0 with one valid value' );
+
+ v = acc( NaN );
+ t.strictEqual( v, 0.0, 'still returns 0.0 after NaN input' );
+
+ v = acc( 4.0 );
+ t.strictEqual( v, 1.0, 'returns correct variance after second valid input' );
+
+ t.end();
+});