diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/README.md b/lib/node_modules/@stdlib/stats/incr/nanapcorr/README.md
new file mode 100644
index 000000000000..20a6de774058
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/README.md
@@ -0,0 +1,176 @@
+
+
+# incrnanapcorr
+
+> Compute a sample absolute [Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values.
+
+
+
+The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables `X` and `Y` is defined as
+
+
+
+```math
+\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y}
+```
+
+
+
+
+
+where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations.
+
+For a sample of size `n`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
+
+
+
+```math
+r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
+```
+
+
+
+
+
+The sample **absolute** [Pearson product-moment correlation coefficient][pearson-correlation] is thus defined as the absolute value of the sample [Pearson product-moment correlation coefficient][pearson-correlation].
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var incrnanapcorr = require( '@stdlib/stats/incr/nanapcorr' );
+```
+
+#### incrnanapcorr( \[mx, my] )
+
+Returns an accumulator `function` which incrementally computes a sample absolute [Pearson product-moment correlation coefficient][pearson-correlation], ignoring `NaN` values.
+
+```javascript
+var accumulator = incrnanapcorr();
+```
+
+If the means are already known, provide `mx` and `my` arguments.
+
+```javascript
+var accumulator = incrnanapcorr( 3.0, -5.5 );
+```
+
+#### accumulator( \[x, y] )
+
+If provided input value `x` and `y`, the accumulator function returns an updated accumulated value. If not provided input values `x` and `y`, the accumulator function returns the current accumulated value.
+
+```javascript
+var accumulator = incrnanapcorr();
+
+var v = accumulator( 2.0, 1.0 );
+// returns 0.0
+
+v = accumulator( 1.0, -5.0 );
+// returns 1.0
+
+v = accumulator( NaN, -5.0 );
+// returns 1.0
+
+v = accumulator( 3.0, 3.14 );
+// returns ~0.965
+
+v = accumulator();
+// returns ~0.965
+```
+
+
+
+
+
+
+
+## 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.
+- In comparison to the sample [Pearson product-moment correlation coefficient][pearson-correlation], the sample absolute [Pearson product-moment correlation coefficient][pearson-correlation] is useful when only concerned with the strength of the correlation and not the direction.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var incrnanapcorr = require( '@stdlib/stats/incr/nanapcorr' );
+
+var accumulator;
+var x;
+var y;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanapcorr();
+
+// For each simulated datum, update the sample absolute correlation coefficient...
+for ( i = 0; i < 100; i++ ) {
+ x = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 );
+ y = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 );
+ accumulator( x, y );
+}
+console.log( accumulator() );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
+
+[covariance]: https://en.wikipedia.org/wiki/Covariance
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanapcorr/benchmark/benchmark.js
new file mode 100644
index 000000000000..044a2653f08c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/benchmark/benchmark.js
@@ -0,0 +1,92 @@
+/**
+* @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 incrnanapcorr = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var f;
+ var i;
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ f = incrnanapcorr();
+ 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 = incrnanapcorr();
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = acc( randu(), 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_means', pkg ), function benchmark( b ) {
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanapcorr( 3.0, -2.0 );
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = acc( randu(), 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/nanapcorr/docs/img/equation_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/img/equation_pearson_correlation_coefficient.svg
new file mode 100644
index 000000000000..61e3ef3e3500
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/img/equation_pearson_correlation_coefficient.svg
@@ -0,0 +1,48 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg
new file mode 100644
index 000000000000..31facfed161b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg
@@ -0,0 +1,126 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/repl.txt
new file mode 100644
index 000000000000..f2913be60cc4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/repl.txt
@@ -0,0 +1,40 @@
+
+{{alias}}( [mx, my] )
+ Returns an accumulator function which incrementally computes the absolute
+ value of the sample Pearson product-moment correlation coefficient, ignoring
+ `NaN` values.
+
+ If provided values, the accumulator function returns an updated accumulated
+ value. If not provided values, the accumulator function returns the current
+ accumulated value.
+
+ Parameters
+ ----------
+ mx: number (optional)
+ Known mean.
+
+ my: number (optional)
+ Known mean.
+
+ Returns
+ -------
+ acc: Function
+ Accumulator function.
+
+ Examples
+ --------
+ > var accumulator = {{alias}}();
+ > var ar = accumulator()
+ null
+ > ar = accumulator( 2.0, 1.0 )
+ 0.0
+ > ar = accumulator( NaN, 1.0 )
+ 0.0
+ > ar = accumulator( -5.0, 3.14 )
+ ~1.0
+ > ar = accumulator()
+ ~1.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/types/index.d.ts
new file mode 100644
index 000000000000..d374c7f66112
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/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
+
+///
+
+/**
+* If provided arguments, returns an updated sample absolute Pearson product-moment correlation coefficient; otherwise, returns the current sample absolute Pearson product-moment correlation coefficient.
+*
+* @param x - value
+* @param y - value
+* @returns sample absolute Pearson product-moment correlation coefficient
+*/
+type accumulator = ( x?: number, y?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes a sample absolute Pearson product-moment correlation coefficient, ignoring `NaN` values.
+*
+* @param meanx - mean value
+* @param meany - mean value
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanapcorr( 2.0, -3.0 );
+*/
+declare function incrnanapcorr( meanx: number, meany: number ): accumulator;
+
+/**
+* Returns an accumulator function which incrementally computes a sample absolute Pearson product-moment correlation coefficient.
+*
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanapcorr();
+*
+* var ar = accumulator();
+* // returns null
+*
+* ar = accumulator( 2.0, 1.0 );
+* // returns 0.0
+*
+* ar = accumulator( NaN, 1.0 );
+* // returns 0.0
+*
+* ar = accumulator( -5.0, 3.14 );
+* // returns ~1.0
+*
+* ar = accumulator();
+* // returns ~1.0
+*/
+declare function incrnanapcorr(): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanapcorr;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/types/test.ts
new file mode 100644
index 000000000000..db2f925a222e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/docs/types/test.ts
@@ -0,0 +1,113 @@
+/*
+* @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 incrnanapcorr = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+ incrnanapcorr(); // $ExpectType accumulator
+ incrnanapcorr( 2, 4 ); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided non-numeric arguments...
+{
+ incrnanapcorr( 2, '5' ); // $ExpectError
+ incrnanapcorr( 2, true ); // $ExpectError
+ incrnanapcorr( 2, false ); // $ExpectError
+ incrnanapcorr( 2, null ); // $ExpectError
+ incrnanapcorr( 2, undefined ); // $ExpectError
+ incrnanapcorr( 2, [] ); // $ExpectError
+ incrnanapcorr( 2, {} ); // $ExpectError
+ incrnanapcorr( 2, ( x: number ): number => x ); // $ExpectError
+
+ incrnanapcorr( '5', 4 ); // $ExpectError
+ incrnanapcorr( true, 4 ); // $ExpectError
+ incrnanapcorr( false, 4 ); // $ExpectError
+ incrnanapcorr( null, 4 ); // $ExpectError
+ incrnanapcorr( undefined, 4 ); // $ExpectError
+ incrnanapcorr( [], 4 ); // $ExpectError
+ incrnanapcorr( {}, 4 ); // $ExpectError
+ incrnanapcorr( ( x: number ): number => x, 4 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid number of arguments...
+{
+ incrnanapcorr( 1 ); // $ExpectError
+ incrnanapcorr( 2, 2, 3 ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+ const acc = incrnanapcorr();
+
+ acc(); // $ExpectType number | null
+ acc( 3.14, 2.0 ); // $ExpectType number | null
+}
+
+// The function returns an accumulator function which returns an accumulated result (known means)...
+{
+ const acc = incrnanapcorr( 2, -3 );
+
+ acc(); // $ExpectType number | null
+ acc( 3.14, 2.0 ); // $ExpectType number | null
+}
+
+// The compiler throws an error if the returned accumulator function is provided invalid arguments...
+{
+ const acc = incrnanapcorr();
+
+ 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
+}
+
+// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)...
+{
+ const acc = incrnanapcorr( 2, -3 );
+
+ 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/nanapcorr/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanapcorr/examples/index.js
new file mode 100644
index 000000000000..28c376a43e36
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/examples/index.js
@@ -0,0 +1,42 @@
+/**
+* @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 uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var incrnanapcorr = require( './../lib' );
+
+var accumulator;
+var ar;
+var x;
+var y;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanapcorr();
+
+// For each simulated datum, update the sample absolute Pearson correlation coefficient...
+console.log( '\nx\ty\t|r|\n' );
+for ( i = 0; i < 100; i++ ) {
+ x = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 );
+ y = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 );
+ ar = accumulator( x, y );
+ console.log( '%d\t%d\t%d', x.toFixed( 4 ), y.toFixed( 4 ), ( ar === null ) ? NaN : ar.toFixed( 4 ) );
+}
+console.log( '\nFinal |r|: %d\n', accumulator() );
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanapcorr/lib/index.js
new file mode 100644
index 000000000000..eccd67766bc1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/lib/index.js
@@ -0,0 +1,54 @@
+/**
+* @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 a sample absolute Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values.
+*
+* @module @stdlib/stats/incr/nanapcorr
+*
+* @example
+* var incrnanapcorr = require( '@stdlib/stats/incr/nanapcorr' );
+*
+* var accumulator = incrnanapcorr();
+*
+* var ar = accumulator();
+* // returns null
+*
+* ar = accumulator( 2.0, 1.0 );
+* // returns 0.0
+*
+* ar = accumulator( NaN, 1.0 );
+* // returns 0.0
+*
+* ar = accumulator( -5.0, 3.14 );
+* // returns ~1.0
+*
+* ar = accumulator();
+* // returns ~1.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanapcorr/lib/main.js
new file mode 100644
index 000000000000..906b5f997f86
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/lib/main.js
@@ -0,0 +1,87 @@
+/**
+* @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 incrapcorr = require( '@stdlib/stats/incr/apcorr' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes a sample absolute Pearson product-moment correlation coefficient, ignoring `NaN` values.
+*
+* @param {number} [meanx] - mean value
+* @param {number} [meany] - mean value
+* @throws {TypeError} first argument must be a number
+* @throws {TypeError} second argument must be a number
+* @returns {Function} accumulator function
+*
+* @example
+* var accumulator = incrnanapcorr();
+*
+* var ar = accumulator();
+* // returns null
+*
+* ar = accumulator( 2.0, 1.0 );
+* // returns 0.0
+*
+* ar = accumulator( NaN, 1.0 );
+* // returns 0.0
+*
+* ar = accumulator( -5.0, 3.14 );
+* // returns ~1.0
+*
+* ar = accumulator();
+* // returns ~1.0
+*
+* @example
+* var accumulator = incrnanapcorr( 2.0, -3.0 );
+*/
+function incrnanapcorr( meanx, meany ) {
+ var acc;
+ if ( arguments.length ) {
+ acc = incrapcorr( meanx, meany );
+ } else {
+ acc = incrapcorr();
+ }
+ return accumulator;
+
+ /**
+ * If provided input values, the accumulator function returns an updated sample correlation coefficient. If not provided input values, the accumulator function returns the current sample correlation coefficient.
+ *
+ * @private
+ * @param {number} [x] - new value
+ * @param {number} [y] - new value
+ * @returns {(number|null)} sample absolute correlation coefficient or null
+ */
+ function accumulator( x, y ) {
+ if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) {
+ return acc();
+ }
+ return acc( x, y );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanapcorr;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/package.json b/lib/node_modules/@stdlib/stats/incr/nanapcorr/package.json
new file mode 100644
index 000000000000..a91814349eb3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/package.json
@@ -0,0 +1,74 @@
+{
+ "name": "@stdlib/stats/incr/nanapcorr",
+ "version": "0.0.0",
+ "description": "Compute a sample absolute Pearson product-moment correlation coefficient, 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",
+ "covariance",
+ "sample covariance",
+ "variance",
+ "unbiased",
+ "var",
+ "correlation",
+ "corr",
+ "pearson",
+ "product-moment",
+ "abs",
+ "absolute",
+ "value",
+ "bivariate",
+ "incremental",
+ "accumulator"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanapcorr/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanapcorr/test/test.js
new file mode 100644
index 000000000000..d864be96eb59
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanapcorr/test/test.js
@@ -0,0 +1,280 @@
+/**
+* @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 isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
+var incrnanapcorr = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof incrnanapcorr, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function throws an error if provided a non-numeric value for the first argument', 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() {
+ incrnanapcorr( value, 5.0 );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a non-numeric value for the second argument', 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() {
+ incrnanapcorr( 3.0, value );
+ };
+ }
+});
+
+tape( 'the function returns an accumulator function', function test( t ) {
+ t.strictEqual( typeof incrnanapcorr(), 'function', 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function returns an accumulator function (known means)', function test( t ) {
+ t.strictEqual( typeof incrnanapcorr( 3.0, -5.0 ), 'function', 'returns expected value' );
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes a sample absolute correlation coefficient', function test( t ) {
+ var expected;
+ var actual;
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0 ];
+ y = [ 1.5, -0.6, 3.14, 4.0, -2.0, 10.0 ];
+
+ // Test against Julia: abs((sum((x[1:n]-mean(x[1:n])).*(y[1:n]-mean(y[1:n]))[:])/(n-1))/(std(x[1:n])*std(y[1:n])))
+ expected = [
+ 0.0,
+ 1.0,
+ 0.8992664495010921,
+ 0.23547201823172273,
+ 0.06765492498103522,
+ 0.4944446711225878
+ ];
+
+ acc = incrnanapcorr();
+
+ for ( i = 0; i < x.length; i++ ) {
+ actual = acc( x[ i ], y[ i ] );
+ t.strictEqual( acc( NaN, y[ i ] ), actual, 'returns expected value' );
+ t.strictEqual( acc( x[ i ], NaN ), actual, 'returns expected value' );
+ t.strictEqual( isAlmostSameValue( actual, expected[ i ], 4 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes a sample absolute correlation coefficient (known means)', function test( t ) {
+ var expected;
+ var actual;
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0 ];
+ y = [ 1.5, -0.6, 3.14, 4.0, -2.0, 10.0 ];
+
+ // Test against Julia: (abs(sum((x[1:n]-3.0).*(y[1:n]-2.6733333333333333)[:])/(n-1))/(stdm(x[1:n],3.0)*stdm(y[1:n],2.6733333333333333)))
+ expected = [
+ 1.0,
+ 0.337429241307504,
+ 0.14242449698664145,
+ 0.31297710227544034,
+ 0.19590456246309015,
+ 0.4944446711225878
+ ];
+
+ acc = incrnanapcorr( 3.0, 2.6733333333333333 );
+
+ for ( i = 0; i < x.length; i++ ) {
+ actual = acc( x[ i ], y[ i ] );
+ t.strictEqual( acc( NaN, y[ i ] ), actual, 'returns expected value' );
+ t.strictEqual( acc( x[ i ], NaN ), actual, 'returns expected value' );
+ t.strictEqual( isAlmostSameValue( actual, expected[ i ], 1 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current sample absolute correlation coefficient', function test( t ) {
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, NaN, 3.0, 1.0, 4.0 ];
+ y = [ 3.14, 1.0, -1.0, 2.4, NaN ];
+
+ acc = incrnanapcorr();
+ for ( i = 0; i < x.length; i++ ) {
+ acc( x[ i ], y[ i ] );
+ }
+ t.strictEqual( acc(), 0.7699852380946451, 'returns expected result' );
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current sample absolute correlation coefficient (known means)', function test( t ) {
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, NaN, 3.0, 1.0, 4.0 ];
+ y = [ 3.14, 1.0, -1.0, 2.4, NaN ];
+
+ acc = incrnanapcorr( 2.0, 1.5133333333333334 );
+ for ( i = 0; i < x.length; i++ ) {
+ acc( x[ i ], y[ i ] );
+ }
+ t.strictEqual( acc(), 0.7699852380946453, 'returns expected result' );
+ t.end();
+});
+
+tape( 'the sample absolute correlation coefficient is `null` until at least 1 datum has been provided (unknown means)', function test( t ) {
+ var acc;
+ var v;
+
+ acc = incrnanapcorr();
+
+ v = acc();
+ t.strictEqual( v, null, 'returns expected value' );
+
+ v = acc( 2.0, 10.0 );
+ t.notEqual( v, null, 'does not return null' );
+
+ v = acc();
+ t.notEqual( v, null, 'does not return null' );
+
+ t.end();
+});
+
+tape( 'the sample absolute correlation coefficient is `null` until at least 1 datum has been provided (known means)', function test( t ) {
+ var acc;
+ var v;
+
+ acc = incrnanapcorr( 3.0, -5.0 );
+
+ v = acc();
+ t.strictEqual( v, null, 'returns expected value' );
+
+ v = acc( 2.0, 10.0 );
+ t.notEqual( v, null, 'does not return null' );
+
+ v = acc();
+ t.notEqual( v, null, 'does not return null' );
+
+ t.end();
+});
+
+tape( 'the sample absolute correlation coefficient is `0` until at least 2 datums have been provided (unknown means)', function test( t ) {
+ var acc;
+ var v;
+
+ acc = incrnanapcorr();
+
+ v = acc( 2.0, 10.0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ v = acc();
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ v = acc( 3.0, -3.14 );
+ t.notEqual( v, 0.0, 'does not return 0' );
+
+ v = acc();
+ t.notEqual( v, 0.0, 'does not return 0' );
+
+ t.end();
+});
+
+tape( 'if only `NaN` values have been provided, the accumulator function returns `null` (unknown means)', function test( t ) {
+ var acc = incrnanapcorr();
+ acc( NaN, 1.0 );
+ acc( 1.0, NaN );
+ acc( NaN, NaN );
+ t.strictEqual( acc(), null, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if only `NaN` values have been provided, the accumulator function returns `null` (known means)', function test( t ) {
+ var acc = incrnanapcorr( 3.0, -5.0 );
+ acc( NaN, 1.0 );
+ acc( 1.0, NaN );
+ acc( NaN, NaN );
+ t.strictEqual( acc(), null, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided `NaN`, the accumulator function ignores the provided values and returns the current sample absolute correlation coefficient', function test( t ) {
+ var acc = incrnanapcorr();
+ t.strictEqual( acc( NaN, 1.0 ), null, 'returns expected value' );
+ t.strictEqual( acc( 1.0, 2.0 ), 0.0, 'returns expected value' );
+ t.strictEqual( acc( NaN, NaN ), 0.0, 'returns expected value' );
+ t.strictEqual( isAlmostSameValue( acc( 2.0, 4.0 ), 1.0, 2 ), true, 'returns expected value' );
+ t.strictEqual( isAlmostSameValue( acc( 5.0, NaN ), 1.0, 2 ), true, 'returns expected value' );
+ t.strictEqual( isAlmostSameValue( acc(), 1.0, 2 ), true, 'returns expected value' );
+ t.end();
+});