feat: add stats/incr/nanmeanstdev

PR-URL: #6148
Closes: #5574

Co-authored-by: AaryaBalwadkarPHC <aarya.dev@projecthumancity.com>
Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>

Author: 3 people

lib/node_modules/@stdlib/stats/incr/nanmeanstdev/README.md

@@ -0,0 +1,218 @@
+<!--
+
+@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.
+
+-->
+
+# incrnanmeanstdev
+
+> Compute an [arithmetic mean][arithmetic-mean] and a [corrected sample standard deviation][sample-stdev] incrementally, ignoring `NaN` values.
+
+<section class="intro">
+
+The [arithmetic mean][arithmetic-mean] is defined as
+
+<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> -->
+
+```math
+\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\bar{x} = \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@5ca648efa8739942a21b07ad7df1947cdd01b662/lib/node_modules/@stdlib/stats/incr/meanstdev/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+and the [corrected sample standard deviation][sample-stdev] is defined as
+
+<!-- <equation class="equation" label="eq:corrected_sample_standard_deviation" align="center" raw="s = \sqrt{\frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2}" alt="Equation for the corrected sample standard deviation."> -->
+
+```math
+s = \sqrt{\frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="s = \sqrt{\frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2}" data-equation="eq:corrected_sample_standard_deviation">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@5ca648efa8739942a21b07ad7df1947cdd01b662/lib/node_modules/@stdlib/stats/incr/meanstdev/docs/img/equation_corrected_sample_standard_deviation.svg" alt="Equation for the corrected sample standard deviation.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var incrnanmeanstdev = require( '@stdlib/stats/incr/nanmeanstdev' );
+```
+
+#### incrnanmeanstdev( \[out] )
+
+Returns an accumulator `function` which incrementally computes an [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][sample-stdev], ignoring `NaN` values.
+
+```javascript
+var accumulator = incrnanmeanstdev();
+```
+
+By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var accumulator = incrnanmeanstdev( new Float64Array( 2 ) );
+```
+
+#### accumulator( \[x] )
+
+If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values.
+
+```javascript
+var accumulator = incrnanmeanstdev();
+
+var ms = accumulator();
+// returns null
+
+ms = accumulator( NaN );
+// returns null
+
+ms = accumulator( 2.0 );
+// returns [ 2.0, 0.0 ]
+
+ms = accumulator( 1.0 );
+// returns [ 1.5, ~0.71 ]
+
+ms = accumulator( 3.0 );
+// returns [ 2.0, 1.0 ]
+
+ms = accumulator( -7.0 );
+// returns [ -0.25, ~4.57 ]
+
+ms = accumulator( -5.0 );
+// returns [ -1.2, ~4.49 ]
+
+ms = accumulator();
+// returns [ -1.2, ~4.49 ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## 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.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ArrayBuffer = require( '@stdlib/array/buffer' );
+var incrnanmeanstdev = require( '@stdlib/stats/incr/nanmeanstdev' );
+
+var offset;
+var acc;
+var buf;
+var out;
+var ms;
+var N;
+var v;
+var i;
+var j;
+
+// Define the number of accumulators:
+N = 5;
+
+// Create an array buffer for storing accumulator output:
+buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element
+
+// Initialize accumulators:
+acc = [];
+for ( i = 0; i < N; i++ ) {
+    // Compute the byte offset:
+    offset = i * 2 * 8; // stride=2, bytes_per_element=8
+
+    // Create a new view for storing accumulated values:
+    out = new Float64Array( buf, offset, 2 );
+
+    // Initialize an accumulator which will write results to the view:
+    acc.push( incrnanmeanstdev( out ) );
+}
+
+// Simulate data and update the sample means and standard deviations...
+for ( i = 0; i < 100; i++ ) {
+    for ( j = 0; j < N; j++ ) {
+        if ( randu() < 0.1 ) {
+            v = NaN;
+        } else {
+            v = randu() * 100.0 * (j+1);
+        }
+        acc[ j ]( v );
+    }
+}
+
+// Print the final results:
+console.log( 'Mean\tStDev' );
+for ( i = 0; i < N; i++ ) {
+    ms = acc[ i ]();
+    console.log( '%d\t%d', ms[ 0 ].toFixed( 3 ), ms[ 1 ].toFixed( 3 ) );
+}
+```
+
+</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
+
+[sample-stdev]: https://en.wikipedia.org/wiki/Standard_deviation
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/stats/incr/nanmeanstdev/benchmark/benchmark.js

@@ -0,0 +1,70 @@
+/**
+* @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 incrnanmeanstdev = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var f;
+	var i;
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		f = incrnanmeanstdev();
+		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 = incrnanmeanstdev();
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		v = acc( randu() );
+		if ( v.length !== 2 ) {
+			b.fail( 'should contain two elements' );
+		}
+	}
+	b.toc();
+	if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});