diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/README.md b/lib/node_modules/@stdlib/stats/incr/nanmvariance/README.md
new file mode 100644
index 000000000000..6a5f7404c455
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/README.md
@@ -0,0 +1,183 @@
+
+
+# incrnanmvariance
+
+> Compute a moving [unbiased sample variance][sample-variance] incrementally, ignoring `NaN` values.
+
+
+
+For a window of size `W`, the [unbiased sample variance][sample-variance] is defined as
+
+
+
+```math
+s^2 = \frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2
+```
+
+
+
+
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var incrnanmvariance = require( '@stdlib/stats/incr/nanmvariance' );
+```
+
+#### incrnanmvariance( window\[, mean] )
+
+Returns an accumulator `function` which incrementally computes a moving [unbiased sample variance][sample-variance]. The `window` parameter defines the number of values over which to compute the moving [unbiased sample variance][sample-variance], ignoring `NaN` values.
+
+```javascript
+var accumulator = incrnanmvariance( 3 );
+```
+
+If the mean is already known, provide a `mean` argument.
+
+```javascript
+var accumulator = incrnanmvariance( 3, 5.0 );
+```
+
+#### accumulator( \[x] )
+
+If provided an input value `x`, the accumulator function returns an updated [unbiased sample variance][sample-variance]. If not provided an input value `x` or provided a `NaN` value, the accumulator function returns the current [unbiased sample variance][sample-variance].
+
+```javascript
+var accumulator = incrnanmvariance( 3 );
+
+var s2 = accumulator();
+// returns null
+
+// Fill the window...
+s2 = accumulator( 2.0 ); // [2.0]
+// returns 0.0
+
+s2 = accumulator( 1.0 ); // [2.0, 1.0]
+// returns 0.5
+
+s2 = accumulator( NaN ); // [2.0, 1.0]
+// returns 0.5
+
+s2 = accumulator( 3.0 ); // [2.0, 1.0, 3.0]
+// returns 1.0
+
+// Window begins sliding...
+s2 = accumulator( -7.0 ); // [1.0, 3.0, -7.0]
+// returns 28.0
+
+s2 = accumulator( -5.0 ); // [3.0, -7.0, -5.0]
+// returns 28.0
+
+s2 = accumulator();
+// returns 28.0
+```
+
+
+
+
+
+
+
+## Notes
+
+- Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for **at least** `W-1` future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
+- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanmvariance = require( '@stdlib/stats/incr/nanmvariance' );
+
+var accumulator;
+var v;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanmvariance( 5 );
+
+// For each simulated datum, update the moving unbiased sample variance...
+for ( i = 0; i < 100; i++ ) {
+ v = randu() * 100.0;
+ accumulator( v );
+}
+console.log( accumulator() );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[sample-variance]: https://en.wikipedia.org/wiki/Variance
+
+
+
+[@stdlib/stats/incr/mmean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mmean
+
+[@stdlib/stats/incr/mstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mstdev
+
+[@stdlib/stats/incr/msummary]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/msummary
+
+[@stdlib/stats/incr/variance]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/variance
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmvariance/benchmark/benchmark.js
new file mode 100644
index 000000000000..5d6350a81788
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/benchmark/benchmark.js
@@ -0,0 +1,92 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2018 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 incrnanmvariance = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var f;
+ var i;
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ f = incrnanmvariance( (i%5)+1 );
+ 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 = incrnanmvariance( 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();
+});
+
+bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) {
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanmvariance( 5, 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/nanmvariance/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/repl.txt
new file mode 100644
index 000000000000..2d2f711b5729
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/repl.txt
@@ -0,0 +1,51 @@
+
+{{alias}}( W[, mean] )
+ Returns an accumulator function which incrementally computes a moving
+ unbiased sample variance, ignoring `NaN` values.
+
+ The `W` parameter defines the number of values over which to compute the
+ moving unbiased sample variance.
+
+ If provided a value, the accumulator function returns an updated moving
+ unbiased sample variance. If not provided a value or provided a `NaN`
+ value, the accumulator function returns the current moving unbiased
+ sample variance.
+
+ As `W` values are needed to fill the window buffer, the first `W-1` returned
+ values are calculated from smaller sample sizes. Until the window is full,
+ each returned value is calculated from all provided values.
+
+ Parameters
+ ----------
+ W: integer
+ Window size.
+
+ mean: number (optional)
+ Known mean.
+
+ Returns
+ -------
+ acc: Function
+ Accumulator function.
+
+ Examples
+ --------
+ > var accumulator = {{alias}}( 3 );
+ > var s2 = accumulator()
+ null
+ > s2 = accumulator( 2.0 )
+ 0.0
+ > s2 = accumulator( -5.0 )
+ 24.5
+ > s2 = accumulator( NaN )
+ 24.5
+ > s2 = accumulator( 3.0 )
+ 19.0
+ > s2 = accumulator( 5.0 )
+ 28.0
+ > s2 = accumulator()
+ 28.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/types/index.d.ts
new file mode 100644
index 000000000000..e64caadc8529
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/types/index.d.ts
@@ -0,0 +1,77 @@
+/*
+* @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, returns an updated unbiased sample variance; otherwise, returns the current unbiased sample variance.
+*
+* ## Notes
+*
+* - If provided `NaN` value which, when used in computations, results in `NaN`, the accumulator returns the current unbiased variance.
+*
+* @param x - value
+* @returns unbiased sample variance
+*/
+type accumulator = ( x?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes a moving unbiased sample variance, ignoring `NaN` values.
+*
+* ## Notes
+*
+* - The `W` parameter defines the number of values over which to compute the moving unbiased sample variance.
+* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
+*
+* @param W - window size
+* @param mean - mean value
+* @throws first argument must be a positive integer
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanmvariance( 3 );
+*
+* var s2 = accumulator();
+* // returns null
+*
+* s2 = accumulator( 2.0 );
+* // returns 0.0
+*
+* s2 = accumulator( -5.0 );
+* // returns 24.5
+*
+* s2 = accumulator( 3.0 );
+* // returns 19.0
+*
+* s2 = accumulator( 5.0 );
+* // returns 28.0
+*
+* s2 = accumulator();
+* // returns 28.0
+*
+* @example
+* var accumulator = incrnanmvariance( 3, -2.0 );
+*/
+declare function incrnanmvariance( W: number, mean?: number ): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanmvariance;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/types/test.ts
new file mode 100644
index 000000000000..ff12831b1236
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/docs/types/test.ts
@@ -0,0 +1,77 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 incrnanmvariance = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+ incrnanmvariance( 3 ); // $ExpectType accumulator
+ incrnanmvariance( 3, 0.0 ); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ incrnanmvariance( '5' ); // $ExpectError
+ incrnanmvariance( true ); // $ExpectError
+ incrnanmvariance( false ); // $ExpectError
+ incrnanmvariance( null ); // $ExpectError
+ incrnanmvariance( [] ); // $ExpectError
+ incrnanmvariance( {} ); // $ExpectError
+ incrnanmvariance( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a number...
+{
+ incrnanmvariance( 3, '5' ); // $ExpectError
+ incrmvariance( 3, true ); // $ExpectError
+ incrnanmvariance( 3, false ); // $ExpectError
+ incrnanmvariance( 3, null ); // $ExpectError
+ incrnanmvariance( 3, [] ); // $ExpectError
+ incrnanmvariance( 3, {} ); // $ExpectError
+ incrnanmvariance( 3, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid number of arguments...
+{
+ incrnanmvariance(); // $ExpectError
+ incrnanmvariance( 3, 2.5, 3 ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+ const acc = incrnanmvariance( 3 );
+
+ 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 = incrnanmvariance( 3 );
+
+ 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/nanmvariance/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmvariance/examples/index.js
new file mode 100644
index 000000000000..77aa13bbb096
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/examples/index.js
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2018 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 incrnanmvariance = require( './../lib' );
+
+var accumulator;
+var s2;
+var v;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanmvariance( 5 );
+
+// For each simulated datum, update the moving unbiased sample variance ignoring `NaN` values...
+console.log( '\nValue\tSample Variance\n' );
+for ( i = 0; i < 100; i++ ) {
+ v = randu() * 100.0;
+ s2 = accumulator( v );
+ console.log( '%d\t%d', v.toFixed( 4 ), s2.toFixed( 4 ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmvariance/lib/index.js
new file mode 100644
index 000000000000..bc1da1b65fc4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/lib/index.js
@@ -0,0 +1,57 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2018 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute a moving unbiased sample variance incrementally.
+*
+* @module @stdlib/stats/incr/nanmvariance
+*
+* @example
+* var incrnanmvariance = require( '@stdlib/stats/incr/nanmvariance' );
+*
+* var accumulator = incrnanmvariance( 3 );
+*
+* var s2 = accumulator();
+* // returns null
+*
+* s2 = accumulator( 2.0 );
+* // returns 0.0
+*
+* s2 = accumulator( -5.0 );
+* // returns 24.5
+*
+* s2 = accumulator( 3.0 );
+* // returns 19.0
+*
+* s2 = accumulator( 5.0 );
+* // returns 28.0
+*
+* s2 = accumulator();
+* // returns 28.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmvariance/lib/main.js
new file mode 100644
index 000000000000..ed6bb2fe8efa
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/lib/main.js
@@ -0,0 +1,90 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2018 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 incrmvariance = require( '@stdlib/stats/incr/mvariance' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes a moving unbiased sample variance, ignoring `NaN` values.
+*
+* @param {PositiveInteger} W - window size
+* @param {number} [mean] - mean value
+* @throws {TypeError} first argument must be a positive integer
+* @throws {TypeError} second argument must be a number
+* @returns {Function} accumulator function
+*
+* @example
+* var accumulator = incrnanmvariance( 3 );
+*
+* var s2 = accumulator();
+* // returns null
+*
+* s2 = accumulator( 2.0 );
+* // returns 0.0
+*
+* s2 = accumulator( -5.0 );
+* // returns 24.5
+*
+* s2 = accumulator( 3.0 );
+* // returns 19.0
+*
+* s2 = accumulator( 5.0 );
+* // returns 28.0
+*
+* s2 = accumulator();
+* // returns 28.0
+*
+* @example
+* var accumulator = incrnanmvariance( 3, -2.0 );
+*/
+function incrnanmvariance( W, mean ) {
+ var acc;
+
+ if ( arguments.length > 1 ) {
+ acc = incrmvariance( W, mean );
+ } else {
+ acc = incrmvariance( W );
+ }
+ return accumulator;
+
+ /**
+ * If provided a value, returns an updated unbiased sample variance. If not provided a value or provided a `NaN` value, returns the current unbiased sample variance.
+ *
+ * @private
+ * @param {number} [x] - input value
+ * @returns {(number|null)} unbiased sample variance or null
+ */
+ function accumulator( x ) {
+ if ( arguments.length === 0 || isnan( x ) ) {
+ return acc();
+ }
+ return acc( x );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanmvariance;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/package.json b/lib/node_modules/@stdlib/stats/incr/nanmvariance/package.json
new file mode 100644
index 000000000000..4ec4f178a2e1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/package.json
@@ -0,0 +1,76 @@
+{
+ "name": "@stdlib/stats/incr/nanmvariance",
+ "version": "0.0.0",
+ "description": "Compute a moving 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",
+ "variance",
+ "sample",
+ "sample variance",
+ "unbiased",
+ "stdev",
+ "standard",
+ "deviation",
+ "dispersion",
+ "incremental",
+ "accumulator",
+ "moving variance",
+ "sliding window",
+ "sliding",
+ "window",
+ "moving",
+ "nan",
+ "ignore"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvariance/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmvariance/test/test.js
new file mode 100644
index 000000000000..57ebd2104575
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmvariance/test/test.js
@@ -0,0 +1,531 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2018 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 randu = require( '@stdlib/random/base/randu' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var zeros = require( '@stdlib/array/base/zeros' );
+var incrnanmvariance = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof incrnanmvariance, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ -5.0,
+ 0.0,
+ 3.14,
+ true,
+ 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() {
+ incrnanmvariance( value );
+ };
+ }
+});
+
+tape( 'the function throws an error if not provided a positive integer for the window size (known mean)', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ -5.0,
+ 0.0,
+ 3.14,
+ true,
+ 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() {
+ incrnanmvariance( value, 3.0 );
+ };
+ }
+});
+
+tape( 'the function throws an error if not provided a number as the mean value', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ 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() {
+ incrnanmvariance( 3, value );
+ };
+ }
+});
+
+tape( 'the function returns an accumulator function', function test( t ) {
+ t.strictEqual( typeof incrnanmvariance( 3 ), 'function', 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function returns an accumulator function (known mean)', function test( t ) {
+ t.strictEqual( typeof incrnanmvariance( 3, 3.0 ), 'function', 'returns expected value' );
+ t.end();
+});
+
+tape( 'the accumulator function computes a moving unbiased sample variance incrementally', function test( t ) {
+ var expected;
+ var actual;
+ var data;
+ var acc;
+ var N;
+ var i;
+
+ data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ];
+ N = data.length;
+
+ acc = incrnanmvariance( 3 );
+
+ actual = zeros( N );
+ for ( i = 0; i < N; i++ ) {
+ actual[ i ] = acc( data[ i ] );
+ }
+ expected = [ 0.0, 0.5, 1.0, 7.0, 7.0, 4.0 ];
+
+ t.deepEqual( actual, expected, 'returns expected incremental results' );
+ t.end();
+});
+
+tape( 'the accumulator function computes a moving unbiased sample variance incrementally (known mean)', function test( t ) {
+ var expected;
+ var actual;
+ var data;
+ var acc;
+ var N;
+ var i;
+
+ data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ];
+ N = data.length;
+
+ acc = incrnanmvariance( 3, 2.0 );
+
+ actual = zeros( N );
+ for ( i = 0; i < N; i++ ) {
+ actual[ i ] = acc( data[ i ] );
+ }
+ expected = [
+ 0.0,
+ 0.5,
+ 1.6666666666666667,
+ 4.666666666666667,
+ 4.666666666666667,
+ 3.6666666666666665
+ ];
+
+ t.deepEqual( actual, expected, 'returns expected incremental results' );
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current unbiased sample variance', function test( t ) {
+ var expected;
+ var actual;
+ var delta;
+ var data;
+ var tol;
+ var acc;
+ var i;
+
+ data = [ 2.0, 3.0, 10.0 ];
+ acc = incrnanmvariance( 3 );
+ for ( i = 0; i < data.length-1; i++ ) {
+ acc( data[ i ] );
+ }
+ t.strictEqual( acc(), 0.5, 'returns current unbiased sample variance' );
+
+ acc( data[ data.length-1 ] );
+
+ expected = 19.0;
+ actual = acc();
+ delta = abs( actual - expected );
+ tol = EPS * expected;
+
+ t.strictEqual( delta < tol, true, 'expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current unbiased sample variance (known mean)', function test( t ) {
+ var expected;
+ var actual;
+ var delta;
+ var data;
+ var tol;
+ var acc;
+ var i;
+
+ data = [ 2.0, 3.0, 10.0 ];
+ acc = incrnanmvariance( 3, 5.0 );
+ for ( i = 0; i < data.length-1; i++ ) {
+ acc( data[ i ] );
+ }
+ t.strictEqual( acc(), 6.5, 'returns current unbiased sample variance' );
+
+ acc( data[ data.length-1 ] );
+
+ expected = 12.666666666666666;
+ actual = acc();
+ delta = abs( actual - expected );
+ tol = EPS * expected;
+
+ t.strictEqual( delta < tol, true, 'expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+ t.end();
+});
+
+tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) {
+ var acc = incrnanmvariance( 3 );
+ t.strictEqual( acc(), null, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if data has yet to be provided, the accumulator function returns `null` (known mean)', function test( t ) {
+ var acc = incrnanmvariance( 3, 3.0 );
+ t.strictEqual( acc(), null, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if only one datum has been provided and the mean is unknown, the accumulator function returns `0`', function test( t ) {
+ var acc = incrnanmvariance( 3 );
+ acc( 2.0 );
+ t.strictEqual( acc(), 0.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if only one datum has been provided and the mean is known, the accumulator function may not return `0`', function test( t ) {
+ var acc = incrnanmvariance( 3, 30 );
+ acc( 2.0 );
+ t.notEqual( acc(), 0.0, 'does not return 0' );
+ t.end();
+});
+
+tape( 'if the window size is `1` and the mean is unknown, the accumulator function always returns `0`', function test( t ) {
+ var acc;
+ var s2;
+ var i;
+
+ acc = incrnanmvariance( 1 );
+ for ( i = 0; i < 100; i++ ) {
+ s2 = acc( randu() * 100.0 );
+ t.strictEqual( s2, 0.0, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'if the window size is `1` and the mean is known, the accumulator function may not always return `0`', function test( t ) {
+ var acc;
+ var s2;
+ var i;
+
+ acc = incrnanmvariance( 1, 500.0 ); // mean is outside the range of simulated values so the variance should never be zero
+ for ( i = 0; i < 100; i++ ) {
+ s2 = acc( randu() * 100.0 );
+ t.notEqual( s2, 0.0, 'does not return 0' );
+ }
+ t.end();
+});
+
+tape( 'if provided `NaN`, the currently accumulated value is returned (unknown mean)', function test( t ) {
+ var expected;
+ var data;
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanmvariance( 3 );
+
+ data = [
+ NaN,
+ 3.14, // 3.14
+ 3.14, // 3.14, 3.14
+ NaN, // 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ 3.14 // 3.14, 3.14, 3.14
+ ];
+ expected = [
+ null,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0
+ ];
+ for ( i = 0; i < data.length; i++ ) {
+ v = acc( data[ i ] );
+ t.strictEqual( v, expected[ i ], 'returns expected value for window '+i );
+ t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i );
+ }
+ t.end();
+});
+
+tape( 'if provided `NaN`, the currently accumulated value is returned (known mean)', function test( t ) {
+ var expected;
+ var data;
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanmvariance( 3, 3.14 );
+
+ data = [
+ NaN,
+ 3.14, // 3.14
+ 3.14, // 3.14, 3.14
+ NaN, // 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ 3.14, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ NaN, // 3.14, 3.14, 3.14
+ 3.14 // 3.14, 3.14, 3.14
+ ];
+ expected = [
+ null,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0
+ ];
+
+ for ( i = 0; i < data.length; i++ ) {
+ v = acc( data[ i ] );
+ t.strictEqual( v, expected[ i ], 'returns expected value for window '+i );
+ t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i );
+ }
+ t.end();
+});
+
+tape( 'if provided `NaN`, the currently accumulated value returned (unknown mean, W=1)', function test( t ) {
+ var expected;
+ var data;
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanmvariance( 1 );
+
+ data = [
+ NaN,
+ 3.14,
+ 3.14,
+ NaN,
+ 3.14,
+ 3.14,
+ 3.14,
+ NaN,
+ 3.14,
+ 3.14,
+ 3.14,
+ NaN,
+ 3.14,
+ 3.14,
+ NaN,
+ NaN,
+ NaN,
+ NaN,
+ 3.14
+ ];
+ expected = [
+ null,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0
+ ];
+
+ for ( i = 0; i < data.length; i++ ) {
+ v = acc( data[ i ] );
+ t.strictEqual( v, expected[ i ], 'returns expected value for window '+i );
+ t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i );
+ }
+ t.end();
+});
+
+tape( 'if provided `NaN`, the currently accumulated value returned (known mean)', function test( t ) {
+ var expected;
+ var data;
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanmvariance( 1, 3.14 );
+
+ data = [
+ NaN,
+ 3.14,
+ 3.14,
+ NaN,
+ 3.14,
+ 3.14,
+ 3.14,
+ NaN,
+ 3.14,
+ 3.14,
+ 3.14,
+ NaN,
+ 3.14,
+ 3.14,
+ NaN,
+ NaN,
+ NaN,
+ NaN,
+ 3.14
+ ];
+ expected = [
+ null,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0,
+ 0.0
+ ];
+ for ( i = 0; i < data.length; i++ ) {
+ v = acc( data[ i ] );
+ t.strictEqual( v, expected[ i ], 'returns expected value for window '+i );
+ t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i );
+ }
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanwmean/benchmark/benchmark.js
new file mode 100644
index 000000000000..e50f87db610b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/benchmark/benchmark.js
@@ -0,0 +1,70 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 incrnanwmean = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var f;
+ var i;
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ f = incrnanwmean();
+ 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 = incrnanwmean();
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = acc( randu(), 1.0 );
+ 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/nanwmean/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/repl.txt
new file mode 100644
index 000000000000..9bd20c5c64ad
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/repl.txt
@@ -0,0 +1,37 @@
+{{alias}}()
+ Returns an accumulator function which incrementally computes a weighted
+ arithmetic mean, ignoring `NaN` values.
+
+ If provided arguments, the accumulator function returns an updated weighted
+ mean. If not provided arguments, the accumulator function returns the
+ current weighted mean.
+
+ If a value is `NaN`, the accumulator function ignores the value and
+ maintains the current state.
+
+ The accumulator function accepts two arguments:
+
+ - x: value.
+ - w: weight.
+
+ Returns
+ -------
+ acc: Function
+ Accumulator function.
+
+ Examples
+ --------
+ > var accumulator = {{alias}}();
+ > var mu = accumulator()
+ null
+ > mu = accumulator( 2.0, 1.0 )
+ 2.0
+ > mu = accumulator( NaN, 1.0 )
+ 2.0
+ > mu = accumulator( 3.0, 1.0 )
+ 2.5
+ > mu = accumulator()
+ 2.5
+
+ See Also
+ --------
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/types/index.d.ts
new file mode 100644
index 000000000000..3cf9249c18c0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/types/index.d.ts
@@ -0,0 +1,64 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 both arguments, returns an updated weighted arithmetic mean; otherwise, returns the current weighted arithmetic mean.
+*
+* ## Notes
+*
+* - If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for all future invocations.
+*
+* @param x - value
+* @param w - weight
+* @returns weighted arithmetic mean
+*/
+type accumulator = ( x?: number, w?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes a weighted arithmetic mean.
+*
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanwmean();
+*
+* var mu = accumulator();
+* // returns null
+*
+* mu = accumulator( 2.0, 1.0 );
+* // returns 2.0
+*
+* mu = accumulator( 2.0, 0.5 );
+* // returns 2.0
+*
+* mu = accumulator( 3.0, 1.5 );
+* // returns 2.5
+*
+* mu = accumulator();
+* // returns 2.5
+*/
+declare function incrnanwmean(): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanwmean;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/types/test.ts
new file mode 100644
index 000000000000..a6d405af525f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/docs/types/test.ts
@@ -0,0 +1,70 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 incrwmean = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+ incrwmean(); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided arguments...
+{
+ incrwmean( '5' ); // $ExpectError
+ incrwmean( 5 ); // $ExpectError
+ incrwmean( true ); // $ExpectError
+ incrwmean( false ); // $ExpectError
+ incrwmean( null ); // $ExpectError
+ incrwmean( undefined ); // $ExpectError
+ incrwmean( [] ); // $ExpectError
+ incrwmean( {} ); // $ExpectError
+ incrwmean( ( x: number ): number => x ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+ const acc = incrwmean();
+
+ acc(); // $ExpectType number | null
+ acc( 3.14, 1.0 ); // $ExpectType number | null
+}
+
+// The compiler throws an error if the returned accumulator function is provided invalid arguments...
+{
+ const acc = incrwmean();
+
+ acc( '5', 1.0 ); // $ExpectError
+ acc( true, 1.0 ); // $ExpectError
+ acc( false, 1.0 ); // $ExpectError
+ acc( null, 1.0 ); // $ExpectError
+ acc( [], 1.0 ); // $ExpectError
+ acc( {}, 1.0 ); // $ExpectError
+ acc( ( x: number ): number => x, 1.0 ); // $ExpectError
+
+ acc( 3.14, '5' ); // $ExpectError
+ acc( 3.14, true ); // $ExpectError
+ acc( 3.14, false ); // $ExpectError
+ acc( 3.14, null ); // $ExpectError
+ acc( 3.14, [] ); // $ExpectError
+ acc( 3.14, {} ); // $ExpectError
+ acc( 3.14, ( x: number ): number => x ); // $ExpectError
+}
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanwmean/examples/index.js
new file mode 100644
index 000000000000..6707465164d2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/examples/index.js
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 incrnanwmean = require( './../lib' );
+
+var accumulator;
+var mu;
+var x;
+var w;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanwmean();
+
+// For each simulated datum, update the weighted mean...
+console.log( '\nValue\tWeight\tWeighted Mean\n' );
+for ( i = 0; i < 100; i++ ) {
+ x = randu() * 100.0;
+ w = randu() * 100.0;
+ mu = accumulator( x, w );
+ console.log( '%d\t%d\t%d', x.toFixed( 4 ), w.toFixed( 4 ), mu.toFixed( 4 ) );
+}
+console.log( '\nFinal weighted mean: %d\n', accumulator() );
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanwmean/lib/index.js
new file mode 100644
index 000000000000..60b564920f27
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/lib/index.js
@@ -0,0 +1,54 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2019 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute a weighted arithmetic mean incrementally, ignoring NaN parameters.
+*
+* @module @stdlib/stats/incr/nanwmean
+*
+* @example
+* var incrnanwmean = require( '@stdlib/stats/incr/nanwmean' );
+*
+* var accumulator = incrnanwmean();
+*
+* var mu = accumulator();
+* // returns null
+*
+* mu = accumulator( 2.0, 1.0 );
+* // returns 2.0
+*
+* mu = accumulator( 2.0, 0.5 );
+* // returns 2.0
+*
+* mu = accumulator( 3.0, 1.5 );
+* // returns 2.5
+*
+* mu = accumulator();
+* // returns 2.5
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanwmean/lib/main.js
new file mode 100644
index 000000000000..bb582a4d5022
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/lib/main.js
@@ -0,0 +1,120 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 incrwmean = require( '@stdlib/stats/incr/wmean' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes a weighted arithmetic mean, ignoring `NaN` parameters.
+*
+* ## Method
+*
+* - The weighted arithmetic mean is defined as
+*
+* ```tex
+* \mu = \frac{\sum_{i=0}^{n-1} w_i x_i}{\sum_{i=0}^{n-1} w_i}
+* ```
+*
+* where \\( w_i \\) are the weights.
+*
+* - The weighted arithmetic mean is equivalent to the simple arithmetic mean when all weights are equal.
+*
+* ```tex
+* \begin{align*}
+* \mu &= \frac{\sum_{i=0}^{n-1} w x_i}{\sum_{i=0}^{n-1} w} \\
+* &= \frac{w\sum_{i=0}^{n-1} x_i}{nw} \\
+* &= \frac{1}{n} \sum_{i=0}^{n-1}
+* \end{align*}
+* ```
+*
+* - If the weights are different, then one can view weights either as sample frequencies or as a means to calculate probabilities where \\( p_i = w_i / \sum w_i \\).
+*
+* - To derive an incremental formula for computing a weighted arithmetic mean, let
+*
+* ```tex
+* W_n = \sum_{i=1}^{n} w_i
+* ```
+*
+* - Accordingly,
+*
+* ```tex
+* \begin{align*}
+* \mu_n &= \frac{1}{W_n} \sum_{i=1}^{n} w_i x_i \\
+* &= \frac{1}{W_n} \biggl(w_n x_n + \sum_{i=1}^{n-1} w_i x_i \biggr) \\
+* &= \frac{1}{W_n} (w_n x_n + W_{n-1} \mu_{n-1}) \\
+* &= \frac{1}{W_n} (w_n x_n + (W_n - w_n) \mu_{n-1}) \\
+* &= \frac{1}{W_n} (W_n \mu_{n-1} + w_n x_n - w_n\mu_{n-1}) \\
+* &= \mu_{n-1} + \frac{w_n}{W_n} (x_n - \mu_{n-1})
+* \end{align*}
+* ```
+*
+* @returns {Function} accumulator function
+*
+* @example
+* var accumulator = incrnanwmean();
+*
+* var mu = accumulator();
+* // returns null
+*
+* mu = accumulator( 2.0, 1.0 );
+* // returns 2.0
+*
+* mu = accumulator( 2.0, 0.5 );
+* // returns 2.0
+*
+* mu = accumulator( 3.0, 1.5 );
+* // returns 2.5
+*
+* mu = accumulator();
+* // returns 2.5
+*/
+function incrnanwmean() {
+ var acc = incrwmean();
+
+ return accumulator;
+
+ /**
+ * If provided arguments, the accumulator function returns an updated weighted mean. If not provided arguments, the accumulator function returns the current weighted mean.
+ *
+ * @private
+ * @param {number} [x] - value
+ * @param {number} [w] - weight
+ * @returns {(number|null)} weighted mean or null
+ */
+ function accumulator( x, w ) {
+ if ( arguments.length === 0 ) {
+ return acc();
+ }
+ if ( isnan( x ) || isnan( w ) ) {
+ return acc();
+ }
+ return acc( x, w );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanwmean;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/package.json b/lib/node_modules/@stdlib/stats/incr/nanwmean/package.json
new file mode 100644
index 000000000000..7826d734f5f7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/package.json
@@ -0,0 +1,69 @@
+{
+ "name": "@stdlib/stats/incr/nanwmean",
+ "version": "0.0.0",
+ "description": "Compute a weighted arithmetic mean 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",
+ "central tendency",
+ "incremental",
+ "accumulator",
+ "weighted",
+ "nan",
+ "ignore"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/incr/nanwmean/test/fixtures/python/data.json
new file mode 100644
index 000000000000..9a1cc4fb45a4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/test/fixtures/python/data.json
@@ -0,0 +1 @@
+[{"step": 1, "x": 3.0471707975443136, "w": 3.9559294497604784, "mean": 3.0471707975443136}, {"step": 2, "x": -10.399841062404956, "w": 3.3577691973009576, "mean": -3.126444550583255}, {"step": 3, "x": 7.5045119580645725, "w": 3.555310355269042, "mean": 0.3509975744077484}, {"step": 4, "x": 9.405647163912139, "w": 3.925572252007643, "mean": 2.753544869877046}, {"step": 5, "x": -19.510351886538363, "w": 2.348687300137866, "mean": -0.2966862687887889}, {"step": 6, "x": -13.021795068623181, "w": 2.88683186016918, "mean": -2.1306885327326004}, {"step": 7, "x": 1.2784040316728538, "w": 0.7850052908255215, "mean": -2.0021205716643617}, {"step": 8, "x": -3.162425923435822, "w": 0.6611973603262699, "mean": -2.0378432392675006}, {"step": 9, "x": -0.16801157504288794, "w": 3.3751745127733113, "mean": -1.7838942273298977}, {"step": 10, "x": -8.5304392757358, "w": 2.4083714101013496, "mean": -2.379942511320534}, {"step": 11, "x": 8.793979748628285, "w": 2.8696569217578256, "mean": -1.3156926211374218}, {"step": 12, "x": 7.777919354289483, "w": 3.8484944013385256, "mean": -0.28571103145409305}, {"step": 13, "x": 0.6603069756121605, "w": 3.2101197680028952, "mean": -0.2040497079223875}, {"step": 14, "x": 11.272412069680328, "w": 2.81253906322418, "mean": 0.6028869213396181}, {"step": 15, "x": 4.675093422520456, "w": 2.8401150876525265, "mean": 0.872852516773853}, {"step": 16, "x": -8.592924628832382, "w": 1.5893554805068, "mean": 0.5342425491363226}, {"step": 17, "x": 3.6875078408249884, "w": 0.2510073893829031, "mean": 0.5519568003899903}, {"step": 18, "x": -9.588826008289988, "w": 2.239915207238576, "mean": 0.0678565402877354}, {"step": 19, "x": 8.784503013072726, "w": 1.1514648968156933, "mean": 0.2766434525404932}, {"step": 20, "x": -0.49925910986252897, "w": 2.1017903542507175, "mean": 0.2441410703285499}, {"step": 21, "x": -1.8486236354526056, "w": 4.281675059014014, "mean": 0.07959462355871812}, {"step": 22, "x": -6.809295444039414, "w": 1.2463034807401698, "mean": -0.07453994202242903}, {"step": 23, "x": 12.225413386740303, "w": 0.3856834342764235, "mean": 0.010039483490497911}, {"step": 24, "x": -1.5452948206880215, "w": 1.4787810709077833, "mean": -0.029914116527385744}, {"step": 25, "x": -4.283278221631072, "w": 1.5386094130567498, "mean": -0.14063615675192645}, {"step": 26, "x": -3.5213355048822956, "w": 3.343390922161786, "mean": -0.32163256326353584}, {"step": 27, "x": 5.323091855533487, "w": 2.829457546472264, "mean": -0.07696426621497057}, {"step": 28, "x": 3.6544406436407835, "w": 3.9411012246214265, "mean": 0.13548865366219276}, {"step": 29, "x": 4.1273261159598835, "w": 3.355136347604199, "mean": 0.3200323834598058}, {"step": 30, "x": 4.308210030078827, "w": 2.0912956210563456, "mean": 0.4317363357791127}, {"step": 31, "x": 21.416476008704613, "w": 4.08869988486357, "mean": 1.5212025421425204}, {"step": 32, "x": -4.064150163846156, "w": 0.9181673075477492, "mean": 1.4568355240616275}, {"step": 33, "x": -5.122427290715374, "w": 0.21128915835591636, "mean": 1.4394336829268486}, {"step": 34, "x": -8.137727282478778, "w": 0.5412345178006446, "mean": 1.3749825600895866}, {"step": 35, "x": 6.159794225754957, "w": 3.639560817922607, "mean": 1.582139838161509}, {"step": 36, "x": 11.289722927208917, "w": 2.3631984282317986, "mean": 1.8475743480392357}, {"step": 37, "x": -1.1394745765487508, "w": 0.8902317172646488, "mean": 1.8171205821224452}, {"step": 38, "x": -8.401564769625281, "w": 2.5551193980064815, "mean": 1.5266007308371616}, {"step": 39, "x": -8.244812156912396, "w": 0.8463293032945253, "mean": 1.435442529141028}, {"step": 40, "x": 6.505927878247011, "w": 3.511969837880907, "mean": 1.6244173800465052}, {"step": 41, "x": 7.432541712034423, "w": 2.2861657503127506, "mean": 1.761991460740914}, {"step": 42, "x": 5.4315426830519495, "w": 1.9670040078727644, "mean": 1.8352822469844088}, {"step": 43, "x": -6.655097072886943, "w": 1.577409236824595, "mean": 1.7014373651904717}, {"step": 44, "x": 2.3216132306671975, "w": 3.188384706282554, "mean": 1.7205884505077298}, {"step": 45, "x": 1.1668580914072821, "w": 1.8728817917116134, "mean": 1.7107231718926006}, {"step": 46, "x": 2.1868859672901295, "w": 0.5294846046488949, "mean": 1.7131094853391238}, {"step": 47, "x": 8.714287779481898, "w": 0.6782289203905251, "mean": 1.7577662372038756}, {"step": 48, "x": 2.2359554877468226, "w": 4.813298556292621, "mean": 1.7784750415795718}, {"step": 49, "x": 6.789135630718949, "w": 4.552045384467275, "mean": 1.9756181293054198}, {"step": 50, "x": 0.6757906948889146, "w": 3.5285649556726733, "mean": 1.9371486375865798}]
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/incr/nanwmean/test/fixtures/python/runner.py
new file mode 100644
index 000000000000..2540b53c5af5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/test/fixtures/python/runner.py
@@ -0,0 +1,88 @@
+#!/usr/bin/env python
+#
+# @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.
+
+"""Generate fixtures."""
+
+import os
+import json
+import numpy as np
+
+# Get the file path:
+FILE = os.path.realpath(__file__)
+
+# Extract the directory in which this file resides:
+DIR = os.path.dirname(FILE)
+
+
+def gen(n, seed, name):
+ """Generate fixture data and write to file.
+
+ # Arguments
+
+ * `n`: number of samples
+ * `seed`: random number generator seed
+ * `name::str`: output filename
+
+ # Examples
+
+ ``` python
+ python> gen(50, 42, './data.json')
+ ```
+ """
+ # Initialize random number generator for reproducibility:
+ rng = np.random.default_rng(seed)
+
+ # Generate data:
+ x = rng.normal(loc=0.0, scale=10.0, size=n)
+ w = rng.uniform(0.1, 5.0, size=n)
+
+ # Store data to be written to file as a list of records:
+ records = []
+
+ for k in range(1, n + 1):
+ x_vals = x[:k]
+ w_vals = w[:k]
+
+ weighted_mean = np.average(x_vals, weights=w_vals)
+
+ records.append({
+ "step": k,
+ "x": float(x[k - 1]),
+ "w": float(w[k - 1]),
+ "mean": float(weighted_mean)
+ })
+
+ # Based on the script directory, create an output filepath:
+ filepath = os.path.join(DIR, name)
+
+ # Write the data to the output filepath as JSON:
+ with open(filepath, "w", encoding="utf-8") as outfile:
+ json.dump(records, outfile)
+
+ # Include trailing newline:
+ with open(filepath, "a", encoding="utf-8") as outfile:
+ outfile.write("\n")
+
+
+def main():
+ """Generate fixture data."""
+ gen(50, 42, "data.json")
+
+
+if __name__ == "__main__":
+ main()
diff --git a/lib/node_modules/@stdlib/stats/incr/nanwmean/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanwmean/test/test.js
new file mode 100644
index 000000000000..97affe57155c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanwmean/test/test.js
@@ -0,0 +1,120 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2019 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 isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
+var incrnanwmean = require( './../lib' );
+
+
+// FIXTURES //
+
+var data = require( './fixtures/python/data.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof incrnanwmean, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function returns an accumulator function', function test( t ) {
+ t.strictEqual( typeof incrnanwmean(), 'function', 'returns expected value' );
+ t.end();
+});
+
+tape( 'the initial accumulated value is `null`', function test( t ) {
+ var acc = incrnanwmean();
+ t.strictEqual( acc(), null, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes a weighted arithmetic mean', function test( t ) {
+ var expected;
+ var actual;
+ var acc;
+ var N;
+ var x;
+ var w;
+ var i;
+
+ N = data.length;
+
+ acc = incrnanwmean();
+
+ for ( i = 0; i < N; i++ ) {
+ x = data[ i ].x;
+ w = data[ i ].w;
+ expected = data[ i ].mean;
+ actual = acc( x, w );
+ t.strictEqual( isAlmostSameValue( actual, expected, 150.0 ), true, 'within tolerance. x: ' + x + '. w: ' + w + '. Value: ' + actual + '. Expected: ' + expected + '.' );
+ }
+ t.end();
+});
+
+tape( 'if not provided arguments, the accumulator function returns the current weighted mean', function test( t ) {
+ var acc;
+ var N;
+ var i;
+
+ N = data.length;
+ acc = incrnanwmean();
+ for ( i = 0; i < N; i++ ) {
+ acc( data[ i ].x, data[ i ].w );
+ }
+ t.strictEqual( isAlmostSameValue( acc(), data[ N - 1 ].mean, 150.0 ), true, 'returns the current accumulated mean' );
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes a weighted arithmetic mean, ignoring NaN values', function test( t ) {
+ var acc = incrnanwmean();
+
+ t.strictEqual( acc( 2.0, 1.0 ), 2.0, 'returns 2.0' );
+ t.strictEqual( acc( NaN, 1.0 ), 2.0, 'ignores NaN, returns 2.0' );
+ t.strictEqual( acc( 3.0, 1.0 ), 2.5, 'returns 2.5' );
+ t.strictEqual( acc(), 2.5, 'returns 2.5' );
+ t.end();
+});
+
+tape( 'if not provided a weight, the accumulator function returns `NaN`', function test( t ) {
+ var acc = incrnanwmean();
+ t.strictEqual( isnan( acc( 2.0 ) ), true, 'returns expected value' );
+ t.strictEqual( isnan( acc( 3.14 ) ), true, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided `NaN` for either a value or a weight, the accumulator function returns `NaN`', function test( t ) {
+ var acc = incrnanwmean();
+ t.strictEqual( acc( 2.0, NaN ), null, 'returns expected value' );
+ t.strictEqual( acc( 3.14, NaN ), null, 'returns expected value' );
+
+ acc = incrnanwmean();
+ t.strictEqual( acc( NaN, 1.0 ), null, 'returns expected value' );
+ t.strictEqual( acc( NaN, 1.0 ), null, 'returns expected value' );
+
+ acc = incrnanwmean();
+ t.strictEqual( acc( NaN, NaN ), null, 'returns expected value' );
+ t.strictEqual( acc( NaN, NaN ), null, 'returns expected value' );
+ t.end();
+});