feat: add stats/incr/nanmme

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

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+<!--
+
+@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.
+
+-->
+
+# incrnanmme
+
+> Compute a moving [mean error][mean-absolute-error] (ME) incrementally, ignoring `NaN` values.
+
+<section class="intro">
+
+For a window of size `W`, the [mean error][mean-absolute-error] is defined **ignoring any `(x, y)` pairs containing NaN**.
+
+```math
+\mathop{\mathrm{ME}} = \frac{1}{W} \sum_{i=0}^{W-1} (y_i - x_i)
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\operatorname{ME} = \frac{1}{W} \sum_{i=0}^{W-1} (y_i - x_i)" data-equation="eq:mean_error">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@634ac3689760e2f57fd51085f387d8dc5bb3b927/lib/node_modules/@stdlib/stats/incr/mme/docs/img/equation_mean_error.svg" alt="Equation for the mean error.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var incrnanmme = require( '@stdlib/stats/incr/nanmme' );
+```
+
+#### incrnanmme( window )
+
+Returns an accumulator `function` which incrementally computes a moving [mean error][mean-absolute-error], ignoring any `(x, y)` pairs containing `NaN`. The `window` parameter defines the number of values over which to compute the moving [mean error][mean-absolute-error].
+
+```javascript
+var accumulator = incrnanmme( 3 );
+```
+
+#### accumulator( \[x, y] )
+
+If provided input values `x` and `y`, the accumulator function returns an updated [mean error][mean-absolute-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean error][mean-absolute-error].
+
+```javascript
+var accumulator = incrnanmme( 3 );
+
+var m = accumulator();
+// returns null
+
+// Fill the window...
+m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)]
+// returns 1.0
+
+m = accumulator( -1.0, 4.0 ); // [(2.0,3.0), (-1.0,4.0)]
+// returns 3.0
+
+m = accumulator( 3.0, NaN ); // ignored
+// returns 3.0
+
+// Window begins sliding...
+m = accumulator( -7.0, 3.0 );
+// returns ~5.33
+
+m = accumulator( -5.0, -3.0 );
+// returns ~5.67
+
+m = accumulator();
+// returns ~5.67
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   Input values are **not** type checked. Any `(x, y)` pair containing `NaN` is ignored and does **not** update the window.
+-   As `W` (x,y) pairs 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.
+-   Be careful when interpreting the [mean error][mean-absolute-error] as errors can cancel. This stated, that errors can cancel makes the [mean error][mean-absolute-error] suitable for measuring the bias in forecasts.
+-   **Warning**: the [mean error][mean-absolute-error] is scale-dependent and, thus, the measure should **not** be used to make comparisons between datasets having different scales.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanmme = require( '@stdlib/stats/incr/nanmme' );
+
+var accumulator;
+var v1;
+var v2;
+var i;
+
+// Initialize an accumulator:
+accumulator = incrnanmme( 5 );
+
+// For each simulated datum, update the moving mean error...
+for ( i = 0; i < 100; i++ ) {
+    v1 = ( randu()*100.0 ) - 50.0;
+    v2 = ( randu()*100.0 ) - 50.0;
+    accumulator( v1, v2 );
+}
+console.log( accumulator() );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[mean-absolute-error]: https://en.wikipedia.org/wiki/Mean_absolute_error
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->
+

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

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+/**
+* @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 incrnanmme = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var f;
+	var i;
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		f = incrnanmme( (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( format( '%s::accumulator-nan', pkg ), function benchmark( b ) {
+	var acc;
+	var v;
+	var i;
+
+	acc = incrnanmme( 5 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		if ( i%10 === 0 ) {
+			v = acc( NaN, randu()-0.5 );
+		} else {
+			v = acc( randu()-0.5, randu()-0.5 );
+		}
+		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();
+});

lib/node_modules/@stdlib/stats/incr/nanmme/docs/repl.txt

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+{{alias}}( W )
+    Returns an accumulator function which incrementally computes a moving
+    mean error (ME), ignoring `NaN` values.
+
+    The `W` parameter defines the number of values over which to compute the
+    moving mean error.
+
+    If provided a value, the accumulator function returns an updated moving
+    mean error. If not provided a value, the accumulator function returns the
+    current moving mean error.
+
+    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 which are not `NaN`.
+
+    Parameters
+    ----------
+    W: integer
+        Window size.
+
+    Returns
+    -------
+    acc: Function
+        Accumulator function.
+
+    Examples
+    --------
+    > var accumulator = {{alias}}( 3 );
+    > var m = accumulator()
+    null
+    > m = accumulator( 2.0, 3.0 )
+    1.0
+    > m = accumulator( -5.0, NaN )
+    1.0
+    > m = accumulator( 3.0, 2.0 )
+    0.0
+    > m = accumulator( 5.0, -2.0 )
+    ~-2.33
+    > m = accumulator()
+    ~-2.33
+
+    See Also
+    --------
+

lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/index.d.ts

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+/*
+* @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.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+/**
+* If provided input values, the accumulator function returns an updated mean error. If not provided input values, the accumulator function returns the current mean error.
+*
+* ## Notes
+*
+* -   If either `x` or `y` is `NaN`, the accumulator ignores the input values and returns the previously accumulated value.
+*
+* @param x - input value
+* @param y - input value
+* @returns mean error or null
+*/
+type accumulator = ( x?: number, y?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes a moving mean error, ignoring 'NaN' values.
+*
+* ## Notes
+*
+* -   The `W` parameter defines the number of values over which to compute the moving mean error.
+* -   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.
+*
+* @param W - window size
+* @throws must provide a positive integer
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanmme( 3 );
+*
+* var m = accumulator();
+* // returns null
+*
+* m = accumulator( 2.0, 3.0 );
+* // returns 1.0
+*
+* m = accumulator( -5.0, 2.0 );
+* // returns 4.0
+*
+* m = accumulator( 3.0, 2.0 );
+* // returns ~2.33
+*
+* m = accumulator( 5.0, -2.0 );
+* // returns ~-0.33
+*
+* m = accumulator();
+* // returns ~-0.33
+*/
+declare function incrnanmme( W: number ): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanmme;
+