diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/README.md b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/README.md
new file mode 100644
index 000000000000..0dfa18f16dc1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/README.md
@@ -0,0 +1,183 @@
+
+
+# incrnanpcorrdist
+
+> Compute a [sample Pearson product-moment correlation distance][pearson-correlation] incrementally, ignoring `NaN` value.
+
+
+
+The [sample Pearson product-moment correlation distance][pearson-correlation] is defined as
+
+
+
+```math
+d_{x,y} = 1 - r_{x,y} = 1 - \frac{\mathop{\mathrm{cov_n(x,y)}}}{\sigma_x \sigma_y}
+```
+
+
+
+
+
+where `r` is the [sample Pearson product-moment correlation coefficient][pearson-correlation], `cov(x,y)` is the sample covariance, and `σ` corresponds to the sample standard deviation. As `r` resides on the interval `[-1,1]`, `d` resides on the interval `[0,2]`.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var incrnanpcorrdist = require( '@stdlib/stats/incr/nanpcorrdist' );
+```
+
+#### incrnanpcorrdist( \[mx, my] )
+
+Returns an accumulator `function` which incrementally computes a [sample Pearson product-moment correlation distance][pearson-correlation], ignoring `NaN` value.
+
+```javascript
+var accumulator = incrnanpcorrdist();
+```
+
+If the means are already known, provide `mx` and `my` arguments.
+
+```javascript
+var accumulator = incrnanpcorrdist( 3.0, -5.5 );
+```
+
+#### accumulator( \[x, y] )
+
+If provided input value `x` and `y`, the accumulator function returns an updated [sample correlation coefficient][pearson-correlation]. If not provided input values `x` and `y`, the accumulator function returns the current [sample correlation coefficient][pearson-correlation].
+
+```javascript
+var accumulator = incrnanpcorrdist();
+
+var d = accumulator( 2.0, 1.0 );
+// returns 1.0
+
+d = accumulator( NaN, 1.0 );
+// returns 1.0
+
+d = accumulator( 1.0, -5.0 );
+// returns 0.0
+
+d = accumulator( 1.0, NaN );
+// returns 0.0
+
+d = accumulator( 3.0, 3.14 );
+// returns ~0.035
+
+d = accumulator();
+// returns ~0.035
+```
+
+
+
+
+
+
+
+## Notes
+
+- Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulator function skips updating its state and continues to return the most recent valid accumulated value. 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 incrnanpcorrdist = require( '@stdlib/stats/incr/nanpcorrdist' );
+
+var accumulator;
+var x;
+var y;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanpcorrdist();
+
+// For each simulated datum, update the sample correlation distance...
+for ( i = 0; i < 100; i++ ) {
+ if ( randu() < 0.2 ) {
+ x = NaN;
+ } else {
+ x = randu() * 100.0;
+ }
+ if ( randu() < 0.2 ) {
+ y = NaN;
+ } else {
+ y = randu() * 100.0;
+ }
+ accumulator( x, y );
+}
+console.log( accumulator() );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
+
+
+
+[@stdlib/stats/incr/covariance]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/covariance
+
+[@stdlib/stats/incr/pcorr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/pcorr
+
+[@stdlib/stats/incr/summary]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/summary
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/benchmark/benchmark.js
new file mode 100644
index 000000000000..a3c41e8eacdf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/benchmark/benchmark.js
@@ -0,0 +1,91 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var randu = require( '@stdlib/random/base/randu' );
+var pkg = require( './../package.json' ).name;
+var incrnanpcorrdist = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var f;
+ var i;
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ f = incrnanpcorrdist();
+ 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( pkg+'::accumulator', function benchmark( b ) {
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanpcorrdist();
+
+ 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( pkg+'::accumulator,known_means', function benchmark( b ) {
+ var acc;
+ var v;
+ var i;
+
+ acc = incrnanpcorrdist( 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/nanpcorrdist/docs/img/equation_pearson_distance.svg b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/img/equation_pearson_distance.svg
new file mode 100644
index 000000000000..6df633f17b81
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/img/equation_pearson_distance.svg
@@ -0,0 +1,70 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/repl.txt
new file mode 100644
index 000000000000..f605e1b8a16b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/repl.txt
@@ -0,0 +1,47 @@
+
+{{alias}}( [mx, my] )
+ Returns an accumulator function which incrementally computes a sample
+ Pearson product-moment correlation distance, ignoring `NaN` value.
+
+ The correlation distance is defined as one minus the Pearson product-moment
+ correlation coefficient and, thus, resides on the interval [0,2].
+
+ If provided values, the accumulator function returns an updated sample
+ correlation distance. If not provided values, the accumulator function
+ returns the current sample correlation distance.
+
+ If provided `NaN` or a value which, when used in computations, results in
+ `NaN`, the accumulated value is `NaN` for all future invocations.
+
+ Parameters
+ ----------
+ mx: number (optional)
+ Known mean.
+
+ my: number (optional)
+ Known mean.
+
+ Returns
+ -------
+ acc: Function
+ Accumulator function.
+
+ Examples
+ --------
+ > var accumulator = {{alias}}();
+ > var d = accumulator()
+ null
+ > d = accumulator( 2.0, 1.0 )
+ ~1.0
+ > d = accumulator( NaN, 1.0 )
+ ~1.0
+ > d = accumulator( -5.0, 3.14 )
+ ~2.0
+ > d = accumulator( -5.0, NaN )
+ ~2.0
+ > d = accumulator()
+ ~2.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/index.d.ts
new file mode 100644
index 000000000000..44dfcc89d6f3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/index.d.ts
@@ -0,0 +1,80 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+/**
+* If provided input values, the accumulator function returns an updated sample correlation distance. If not provided input values, the accumulator function returns the current sample correlation distance.
+*
+* ## Notes
+*
+* - The correlation distance is defined as one minus the Pearson product-moment correlation coefficient and, thus, resides on the interval [0,2].
+* - 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 y - value
+* @returns updated sample correlation distance
+*/
+type accumulator = ( x?: number, y?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance, ignoring `NaN` value.
+*
+* @param meanx - mean value
+* @param meany - mean value
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanpcorrdist( 2.0, -3.0 );
+*/
+declare function incrnanpcorrdist( meanx: number, meany: number ): accumulator;
+
+/**
+* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance.
+*
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanpcorrdist();
+*
+* var d = accumulator();
+* // returns null
+*
+* d = accumulator( 2.0, 1.0 );
+* // returns 1.0
+*
+* d = accumulator( NaN, 1.0 );
+* // returns 1.0
+*
+* d = accumulator( -5.0, 3.14 );
+* // returns ~2.0
+*
+* d = accumulator( -5.0, NaN );
+* // returns ~2.0
+*
+* d = accumulator();
+* // returns ~2.0
+*/
+declare function incrnanpcorrdist(): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanpcorrdist;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/test.ts
new file mode 100644
index 000000000000..72712fcc3cb5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/test.ts
@@ -0,0 +1,113 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import incrnanpcorrdist = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+ incrnanpcorrdist(); // $ExpectType accumulator
+ incrnanpcorrdist( 2, 4 ); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided non-numeric arguments...
+{
+ incrnanpcorrdist( 2, '5' ); // $ExpectError
+ incrnanpcorrdist( 2, true ); // $ExpectError
+ incrnanpcorrdist( 2, false ); // $ExpectError
+ incrnanpcorrdist( 2, null ); // $ExpectError
+ incrnanpcorrdist( 2, undefined ); // $ExpectError
+ incrnanpcorrdist( 2, [] ); // $ExpectError
+ incrnanpcorrdist( 2, {} ); // $ExpectError
+ incrnanpcorrdist( 2, ( x: number ): number => x ); // $ExpectError
+
+ incrnanpcorrdist( '5', 4 ); // $ExpectError
+ incrnanpcorrdist( true, 4 ); // $ExpectError
+ incrnanpcorrdist( false, 4 ); // $ExpectError
+ incrnanpcorrdist( null, 4 ); // $ExpectError
+ incrnanpcorrdist( undefined, 4 ); // $ExpectError
+ incrnanpcorrdist( [], 4 ); // $ExpectError
+ incrnanpcorrdist( {}, 4 ); // $ExpectError
+ incrnanpcorrdist( ( x: number ): number => x, 4 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid number of arguments...
+{
+ incrnanpcorrdist( 1 ); // $ExpectError
+ incrnanpcorrdist( 2, 2, 3 ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+ const acc = incrnanpcorrdist();
+
+ 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 = incrnanpcorrdist( 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 = incrnanpcorrdist();
+
+ 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 = incrnanpcorrdist( 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/nanpcorrdist/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/examples/index.js
new file mode 100644
index 000000000000..a664ef6cc6a0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/examples/index.js
@@ -0,0 +1,49 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanpcorrdist = require( './../lib' );
+
+var accumulator;
+var d;
+var x;
+var y;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanpcorrdist();
+
+// For each simulated datum, update the sample Pearson correlation distance...
+console.log( '\nx\ty\tCorrelation Distance\n' );
+for ( i = 0; i < 100; i++ ) {
+ if ( randu() < 0.2 ) {
+ x = NaN;
+ } else {
+ x = randu() * 100.0;
+ }
+ if ( randu() < 0.2 ) {
+ y = NaN;
+ } else {
+ y = randu() * 100.0;
+ }
+ d = accumulator( x, y );
+ console.log( '%d\t%d\t%d', x.toFixed( 4 ), y.toFixed( 4 ), d.toFixed( 4 ) );
+}
+console.log( '\nFinal 1-r: %d\n', accumulator() );
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/index.js
new file mode 100644
index 000000000000..787eff16f5ce
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/index.js
@@ -0,0 +1,57 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute a sample Pearson product-moment correlation distance incrementally.
+*
+* @module @stdlib/stats/incr/nanpcorrdist
+*
+* @example
+* var incrnanpcorrdist = require( '@stdlib/stats/incr/nanpcorrdist' );
+*
+* var accumulator = incrnanpcorrdist();
+*
+* var d = accumulator();
+* // returns null
+*
+* d = accumulator( 2.0, 1.0 );
+* // returns 1.0
+*
+* d = accumulator( NaN, 1.0 );
+* // returns 1.0
+*
+* d = accumulator( -5.0, 3.14 );
+* // returns ~2.0
+*
+* d = accumulator( -5.0, NaN );
+* // returns ~2.0
+*
+* d = accumulator();
+* // returns ~2.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/main.js
new file mode 100644
index 000000000000..1aa5f43b13af
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/main.js
@@ -0,0 +1,101 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
+var incrpcorrdist = require( '@stdlib/stats/incr/pcorrdist' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance, ignoring `NaN` value.
+*
+* ## Method
+*
+* - The sample Pearson product-moment correlation distance is defined as
+*
+* ```tex
+* d = 1 - r = 1 - \frac{\operatorname{cov}_n(x,y)}{\sigma_x \sigma_y}
+* ```
+*
+* - The implementation thus computes the sample Pearson product-moment correlation coefficient \\(r\\) and subtracts the coefficient from 1.
+*
+* @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 = incrnanpcorrdist();
+*
+* var d = accumulator();
+* // returns null
+*
+* d = accumulator( 2.0, 1.0 );
+* // returns 1.0
+*
+* d = accumulator( NaN, 1.0 );
+* // returns 1.0
+*
+* d = accumulator( -5.0, 3.14 );
+* // returns ~2.0
+*
+* d = accumulator( -5.0, NaN );
+* // returns ~2.0
+*
+* d = accumulator();
+* // returns ~2.0
+*
+* @example
+* var accumulator = incrnanpcorrdist( 2.0, -3.0 );
+*/
+function incrnanpcorrdist( meanx, meany ) {
+ var pcorrdist;
+ if ( arguments.length > 0 ) {
+ pcorrdist = incrpcorrdist( meanx, meany );
+ } else {
+ pcorrdist = incrpcorrdist();
+ }
+ return accumulator;
+
+ /**
+ * If provided input values, the accumulator function returns an updated sample correlation distance. If not provided input values, the accumulator function returns the current sample correlation distance.
+ *
+ * @private
+ * @param {number} [x] - new value
+ * @param {number} [y] - new value
+ * @returns {(number|null)} sample correlation distance or null
+ */
+ function accumulator( x, y ) {
+ if ( arguments.length === 0 || isnan( x ) || !isNumber( x ) || isnan( y ) || !isNumber( y ) ) {
+ return pcorrdist();
+ }
+ return pcorrdist( x, y );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanpcorrdist;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/package.json b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/package.json
new file mode 100644
index 000000000000..00095e0e995d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/package.json
@@ -0,0 +1,71 @@
+{
+ "name": "@stdlib/stats/incr/nanpcorrdist",
+ "version": "0.0.0",
+ "description": "Compute a sample Pearson product-moment correlation distance.",
+ "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",
+ "correlation",
+ "corr",
+ "pcorr",
+ "ppmcc",
+ "pcc",
+ "pearson",
+ "product-moment",
+ "bivariate",
+ "distance",
+ "dist",
+ "incremental",
+ "accumulator"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/test/test.js
new file mode 100644
index 000000000000..da600bfe6936
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/test/test.js
@@ -0,0 +1,324 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var incrnanpcorrdist = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof incrnanpcorrdist, '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() {
+ incrnanpcorrdist( 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() {
+ incrnanpcorrdist( 3.0, value );
+ };
+ }
+});
+
+tape( 'the function returns an accumulator function', function test( t ) {
+ t.equal( typeof incrnanpcorrdist(), 'function', 'returns a function' );
+ t.end();
+});
+
+tape( 'the function returns an accumulator function (known means)', function test( t ) {
+ t.equal( typeof incrnanpcorrdist( 3.0, -5.0 ), 'function', 'returns a function' );
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes a sample correlation distance', function test( t ) {
+ var expected;
+ var actual;
+ var delta;
+ var tol;
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, 3.0, NaN, 2.0, 4.0, 3.0, 4.0 ];
+ y = [ 1.5, -0.6, 3.14, 3.14, 4.0, -2.0, 10.0 ];
+
+ // Test against Julia: 1.0-(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 = [
+ 1.0,
+ 2.0,
+ 2.0,
+ 1.8992664495010921,
+ 0.7645279817682773,
+ 0.9323450750189648,
+ 0.5055553288774122
+ ];
+
+ acc = incrnanpcorrdist();
+
+ for ( i = 0; i < x.length; i++ ) {
+ actual = acc( x[ i ], y[ i ] );
+ if ( actual === expected[ i ] ) {
+ t.strictEqual( actual, expected[ i ], 'returns expected result. x: '+x[i]+'. y: '+y[i]+'.' );
+ } else {
+ delta = abs( expected[ i ] - actual );
+ tol = 3.7 * EPS * abs( expected[ i ] );
+ t.equal( delta <= tol, true, 'x: '+x[i]+'. y: '+y[i]+'. expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+ }
+ }
+ t.end();
+});
+
+tape( 'the accumulator function incrementally computes a sample correlation distance (known means)', function test( t ) {
+ var expected;
+ var actual;
+ var delta;
+ var tol;
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, 3.0, NaN, 2.0, 4.0, 3.0, 4.0 ];
+ y = [ 1.5, -0.6, 3.12, 3.14, 4.0, -2.0, 10.0 ];
+
+ // Test against Julia: 1.0-(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 = [
+ 0.0,
+ 0.662570758692496,
+ 0.662570758692496,
+ 0.8575755030133585,
+ 0.6870228977245596,
+ 0.8040954375369098,
+ 0.5055553288774122
+ ];
+
+ acc = incrnanpcorrdist( 3.0, 2.6733333333333333 );
+
+ for ( i = 0; i < x.length; i++ ) {
+ actual = acc( x[ i ], y[ i ] );
+ if ( actual === expected[ i ] ) {
+ t.strictEqual( actual, expected[ i ], 'returns expected result. x: '+x[i]+'. y: '+y[i]+'.' );
+ } else {
+ delta = abs( expected[ i ] - actual );
+ tol = EPS * abs( expected[ i ] );
+ t.equal( delta <= tol, true, 'x: '+x[i]+'. y: '+y[i]+'. expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+ }
+ }
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current sample correlation distance', function test( t ) {
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, NaN, 3.0, 1.0 ];
+ y = [ 3.14, 2.14, -1.0, 2.4];
+
+ acc = incrnanpcorrdist();
+ for ( i = 0; i < x.length; i++ ) {
+ acc( x[ i ], y[ i ] );
+ }
+ t.equal( acc(), 1.7699852380946451, 'returns expected result' );
+ t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current sample correlation distance (known means)', function test( t ) {
+ var acc;
+ var x;
+ var y;
+ var i;
+
+ x = [ 2.0, NaN, 3.0, 1.0 ];
+ y = [ 3.14, 2.2, -1.0, 2.4 ];
+
+ acc = incrnanpcorrdist( 2.0, 1.5133333333333334 );
+ for ( i = 0; i < x.length; i++ ) {
+ acc( x[ i ], y[ i ] );
+ }
+ t.equal( acc(), 1.7699852380946453, 'returns expected result' );
+ t.end();
+});
+
+tape( 'the sample correlation distance is `null` until at least 1 datum has been provided (unknown means)', function test( t ) {
+ var acc;
+ var v;
+
+ acc = incrnanpcorrdist();
+
+ v = acc();
+ t.equal( v, null, 'returns null' );
+
+ v = acc( 3.0, -3.14 );
+ t.notEqual( v, null, 'does not return null' );
+
+ t.end();
+});
+
+tape( 'the sample correlation distance is `null` until at least 1 datum has been provided (known means)', function test( t ) {
+ var acc;
+ var v;
+
+ acc = incrnanpcorrdist( 3.0, -5.0 );
+
+ v = acc();
+ t.equal( v, null, 'returns null' );
+
+ v = acc( 3.0, -3.14 );
+ t.notEqual( v, null, 'does not return null' );
+
+ t.end();
+});
+
+tape( 'the sample correlation distance is `1` until at least 2 datums have been provided (unknown means)', function test( t ) {
+ var acc;
+ var v;
+
+ acc = incrnanpcorrdist();
+
+ v = acc( 2.0, 10.0 );
+ t.equal( v, 1.0, 'returns 1' );
+
+ v = acc( 3.0, -3.14 );
+ t.notEqual( v, 1.0, 'does not return 1' );
+
+ t.end();
+});
+
+tape( 'if provided a `NaN`, the accumulator function skips updating its state (unknown means)', function test( t ) {
+ var data;
+ var prev;
+ var acc;
+ var v;
+
+ data = [
+ [ 2.0, 1.0 ],
+ [ 1.0, 2.0 ],
+ [ NaN, 1.0 ],
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 0.0 ]
+ ];
+ acc = incrnanpcorrdist();
+
+ v = acc( data[ 0 ][ 0 ], data[ 0 ][ 1 ] );
+ v = acc( data[ 1 ][ 0 ], data[ 1 ][ 1 ] );
+ prev = acc();
+
+ v = acc( data[ 2 ][ 0 ], data[ 2 ][ 1 ] );
+ t.equal( v, prev, 'skips update when first parameter is NaN' );
+ t.equal( acc(), prev, 'state remains unchanged' );
+
+ v = acc( data[ 3 ][ 0 ], data[ 3 ][ 1 ] );
+ prev = v;
+
+ v = acc( 4.0, NaN );
+ t.equal( v, prev, 'skips update when second parameter is NaN' );
+ t.equal( acc(), prev, 'state remains unchanged' );
+
+ t.end();
+});
+
+tape( 'if provided a `NaN`, the accumulator function skips updating its state (known means)', function test( t ) {
+ var data;
+ var prev;
+ var acc;
+ var v;
+
+ data = [
+ [ 2.0, 1.0 ],
+ [ 1.0, 2.0 ],
+ [ NaN, 1.0 ],
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 0.0 ]
+ ];
+ acc = incrnanpcorrdist( 3.14, 1.0 );
+
+ v = acc( data[ 0 ][ 0 ], data[ 0 ][ 1 ] );
+ v = acc( data[ 1 ][ 0 ], data[ 1 ][ 1 ] );
+ prev = acc();
+
+ v = acc( data[ 2 ][ 0 ], data[ 2 ][ 1 ] );
+ t.equal( v, prev, 'skips update when first parameter is NaN' );
+ t.equal( acc(), prev, 'state remains unchanged' );
+
+ v = acc( data[ 3 ][ 0 ], data[ 3 ][ 1 ] );
+ prev = v;
+
+ v = acc( 4.0, NaN );
+ t.equal( v, prev, 'skips update when second parameter is NaN' );
+ t.equal( acc(), prev, 'state remains unchanged' );
+
+ t.end();
+});