feat: add stats/incr/nanmcv

lib/node_modules/@stdlib/stats/incr/nanmcv/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.
+
+-->
+
+# incrnanmcv
+
+> Compute a moving [coefficient of variation][coefficient-of-variation] (CV) incrementally, ignoring `NaN` values.
+
+<section class="intro">
+
+For a window of size `W`, the [corrected sample standard deviation][standard-deviation] is defined as
+
+<!-- <equation class="equation" label="eq:corrected_sample_standard_deviation" align="center" raw="s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2}" alt="Equation for the corrected sample standard deviation."> -->
+
+```math
+s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2}" data-equation="eq:corrected_sample_standard_deviation">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eed6b690d7c37249b04544b3f5fd36ad8eb3187f/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_corrected_sample_standard_deviation.svg" alt="Equation for the corrected sample standard deviation.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+and the [arithmetic mean][arithmetic-mean] is defined as
+
+<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i" alt="Equation for the arithmetic mean."> -->
+
+```math
+\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i" data-equation="eq:arithmetic_mean">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@4cf17e4e25cc2244d5154bd5d251f4bd023748da/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+The [coefficient of variation][coefficient-of-variation] (also known as **relative standard deviation**, RSD) is defined as
+
+<!-- <equation class="equation" label="eq:coefficient_of_variation" align="center" raw="c_v = \frac{s}{\bar{x}}" alt="Equation for the coefficient of variation (CV)."> -->
+
+<div class="equation" align="center" data-raw-text="c_v = \frac{s}{\bar{x}}" data-equation="eq:coefficient_of_variation">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eed6b690d7c37249b04544b3f5fd36ad8eb3187f/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_coefficient_of_variation.svg"Equation for the coefficient of variation (CV).">
+    <br>
+</div>
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var incrnanmcv = require( '@stdlib/stats/incr/nanmcv' );
+```
+
+#### incrnanmcv( window\[, mean] )
+
+Returns an accumulator function which incrementally computes a moving [coefficient of variation][coefficient-of-variation].
+
+```javascript
+var accumulator = incrnanmcv( 3 );
+```
+
+The function supports the following parameters:
+
+-   **window**: defines the number of values over which to compute the moving [coefficient of variation][coefficient-of-variation].
+-   **mean**: known mean.
+
+If the mean is already known, provide a `mean` argument.
+
+```javascript
+var accumulator = incrnanmcv( 3, 5.0 );
+```
+
+#### accumulator( \[x] )
+
+If provided an input value `x`, the accumulator function returns an updated accumulated value. If not provided an input value `x`, the accumulator function returns the current accumulated value.
+
+```javascript
+var accumulator = incrnanmcv( 3 );
+
+var cv = accumulator();
+// returns null
+
+// Fill the window...
+cv = accumulator( 2.0 ); // [2.0]
+// returns 0.0
+
+cv = accumulator( NaN ); // [2.0]
+// returns 0.0
+
+cv = accumulator( 3.0 ); // [2.0, 3.0]
+// returns ~0.28
+
+cv = accumulator( 1.0 ); // [2.0, 3.0, 1.0]
+// returns ~0.50
+
+// Window begins sliding...
+cv = accumulator( NaN ); // [2.0, 3.0, 1.0]
+// returns ~0.50
+
+cv = accumulator( 7.0 ); // [3.0, 1.0, 7.0]
+// returns ~0.83
+
+cv = accumulator( 5.0 ); // [1.0, 7.0, 5.0]
+// returns ~0.71
+
+cv = accumulator( NaN ); // [1.0, 7.0, 5.0]
+// returns ~0.71
+
+cv = accumulator();
+// returns ~0.71
+```
+
+</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.
+-   As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
+-   The [coefficient of variation][coefficient-of-variation] is typically computed on nonnegative values. The measure may lack meaning for data which can assume both positive and negative values.
+-   For small and moderately sized samples, the accumulated value tends to be too low and is thus a **biased** estimator. Provided the generating distribution is known (e.g., a normal distribution), you may want to adjust the accumulated value or use an alternative implementation providing an unbiased estimator.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanmcv = require( '@stdlib/stats/incr/nanmcv' );
+
+// Initialize an accumulator with window size 5:
+var accumulator = incrnanmcv( 5 );
+
+// For each simulated datum, update the moving coefficient of variation...
+var i;
+for ( i = 0; i < 100; i++ ) {
+    accumulator( ( randu() < 0.2 ) ? NaN : randu()*100.0 );
+}
+console.log( accumulator() );
+```
+
+</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">
+
+[coefficient-of-variation]: https://en.wikipedia.org/wiki/Coefficient_of_variation
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/stats/incr/nanmcv/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 isnan = require( '@stdlib/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var incrnanmcv = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var f;
+	var i;
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		f = incrnanmcv( (i%5)+1 );
+		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 = incrnanmcv( 5 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		v = acc( i+1 );
+		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();
+});
+
+bench( pkg+'::accumulator,known_mean', function benchmark( b ) {
+	var acc;
+	var v;
+	var i;
+
+	acc = incrnanmcv( 5, 0.5 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		v = acc( i+1 );
+		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();
+});