feat: add stats/base/ndarray/dnanmeanpn

lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/README.md

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+<!--
+
+@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.
+
+-->
+
+# dnanmeanpn
+
+> Compute the [arithmetic mean][arithmetic-mean] of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.
+
+<section class="intro">
+
+The [arithmetic mean][arithmetic-mean] is defined as
+
+<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> -->
+
+```math
+\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" data-equation="eq:arithmetic_mean">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@42d8f64d805113ab899c79c7c39d6c6bac7fe25c/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dnanmeanpn = require( '@stdlib/stats/base/ndarray/dnanmeanpn' );
+```
+
+#### dnanmeanpn( arrays )
+
+Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = dnanmeanpn( [ x ] );
+// returns ~0.3333
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dnanmeanpn = require( '@stdlib/stats/base/ndarray/dnanmeanpn' );
+
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
+    }
+    return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'float64', rand );
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = dnanmeanpn( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+* * *
+
+<section class="references">
+
+## References
+
+-   Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958][@neely:1966a].
+-   Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036][@schubert:2018a].
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[@neely:1966a]: https://doi.org/10.1145/365719.365958
+
+[@schubert:2018a]: https://doi.org/10.1145/3221269.3223036
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/benchmark/benchmark.js

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+/**
+* @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 uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var dnanmeanpn = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = filledarrayBy( len, 'float64', rand );
+	x = new ndarray( 'float64', xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dnanmeanpn( [ x ] );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();

lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/docs/repl.txt

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+
+{{alias}}( arrays )
+    Computes the arithmetic mean of a one-dimensional double-precision floating-
+    point ndarray, ignoring `NaN` values and using a two-pass error correction
+    algorithm.
+
+    If provided an empty ndarray, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        Arithmetic mean.
+
+    Examples
+    --------
+    > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] );
+    > var dt = 'float64';
+    > var sh = [ xbuf.length ];
+    > var sx = [ 1 ];
+    > var ox = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+    > {{alias}}( [ x ] )
+    ~0.3333
+
+    See Also
+    --------

lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/docs/types/index.d.ts

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+/*
+* @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
+
+/// <reference types="@stdlib/types"/>
+
+import { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns arithmetic mean
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanmeanpn( [ x ] );
+* // returns ~0.3333
+*/
+declare function dnanmeanpn( arrays: [ float64ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = dnanmeanpn;