feat: add stats/base/ndarray/sdsmeanors

lib/node_modules/@stdlib/stats/base/ndarray/sdsmeanors/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.
+
+-->
+
+# sdsmeanors
+
+> Compute the [arithmetic mean][arithmetic-mean] of a single-precision floating-point ndarray using ordinary recursive summation with extended accumulation.
+
+<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@develop/lib/node_modules/%40stdlib/stats/base/ndarray/meanors/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var sdsmeanors = require( '@stdlib/stats/base/ndarray/sdsmeanors' );
+```
+
+#### sdsmeanors( arrays )
+
+Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point ndarray using ordinary recursive summation with extended accumulation.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = sdsmeanors( [ x ] );
+// returns 2.5
+```
+
+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`.
+-   Accumulated intermediate values are stored as double-precision floating-point numbers.
+-   Ordinary recursive summation (i.e., "simple" summation) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation to compute the arithmetic mean is acceptable; in all other cases, exercise due caution.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint-disable no-console -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var sdsmeanors = require( '@stdlib/stats/base/ndarray/sdsmeanors' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+    'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = sdsmeanors( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- 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
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/stats/base/ndarray/sdsmeanors/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/array/uniform' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var sdsmeanors = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = uniform( len, -10.0, 10.0, options );
+	x = new ndarray( options.dtype, 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 = sdsmeanors( [ x ] );
+			if ( isnanf( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnanf( 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/sdsmeanors/docs/repl.txt

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+
+{{alias}}( arrays )
+    Computes the arithmetic mean of a single-precision floating-point ndarray
+    using ordinary recursive summation with extended accumulation.
+
+    Accumulated intermediate values are stored as double-precision floating-
+    point numbers.
+
+    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/float32}}( [ 1.0, -2.0, 2.0 ] );
+    > var dt = 'float32';
+    > 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/sdsmeanors/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 { float32ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the arithmetic mean of a single-precision floating-point ndarray using ordinary recursive summation with extended accumulation.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns arithmetic mean
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = sdsmeanors( [ x ] );
+* // returns 2.5
+*/
+declare function sdsmeanors( arrays: [ float32ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = sdsmeanors;