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feat(stats): add nanme package
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‎lib/node_modules/@stdlib/stats/incr/nanme/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2025 The Stdlib Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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# incrnanme
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> Compute the [mean error][mean-absolute-error] (ME) incrementally, ignoring `NaN` values.
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<section class="intro">
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The [mean error][mean-absolute-error] is defined as
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<!-- <equation class="equation" label="eq:mean_error" align="center" raw="\operatorname{ME} = \frac{1}{n} \sum_{i=0}^{n-1} (y_i - x_i)" alt="Equation for the mean error."> -->
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```math
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\mathop{\mathrm{ME}} = \frac{1}{n} \sum_{i=0}^{n-1} (y_i - x_i)
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```
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<!-- <div class="equation" align="center" data-raw-text="\operatorname{ME} = \frac{1}{n} \sum_{i=0}^{n-1} (y_i - x_i)" data-equation="eq:mean_error">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@7d6e6319f451be0997d35a6cf491b08e1f2cb5cf/lib/node_modules/@stdlib/stats/incr/nanme/docs/img/equation_mean_error.svg" alt="Equation for the mean error.">
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<br>
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</div> -->
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<!-- </equation> -->
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</section>
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<!-- /.intro -->
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<section class="usage">
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## Usage
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```javascript
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var incrnanme = require( '@stdlib/stats/incr/nanme' );
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```
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#### incrnanme()
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Returns an accumulator `function` which incrementally computes the [mean error][mean-absolute-error], ignoring `NaN` values.
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```javascript
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var accumulator = incrnanme();
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```
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#### accumulator( \[x, y] )
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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].
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```javascript
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var accumulator = incrnanme();
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var m = accumulator( 2.0, 3.0 );
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// returns 1.0
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m = accumulator( -1.0, -4.0 );
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// returns -1.0
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m = accumulator( -3.0, 5.0 );
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// returns 2.0
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m = accumulator();
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// returns 2.0
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```
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</section>
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<!-- /.usage -->
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<section class="notes">
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## Notes
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- 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.
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- 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.
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- **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.
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</section>
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<!-- /.notes -->
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<section class="examples">
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## Examples
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<!-- eslint no-undef: "error" -->
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```javascript
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var randu = require( '@stdlib/random/base/randu' );
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var incrnanme = require( '@stdlib/stats/incr/nanme' );
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var accumulator;
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var v1;
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var v2;
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var i;
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// Initialize an accumulator:
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accumulator = incrnanme();
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// For each simulated datum, update the mean error...
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for ( i = 0; i < 100; i++ ) {
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if( randu() < 0.2 ){
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v1 = NaN;
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} else {
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v1 = ( randu()*100.0 ) - 50.0;
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}
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if( randu() < 0.2 ){
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v2 = NaN;
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} else {
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v2 = ( randu()*100.0 ) - 50.0;
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}
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}
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console.log( accumulator() );
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```
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</section>
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<!-- /.examples -->
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<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
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<section class="related">
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* * *
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## See Also
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- <span class="package-name">[`@stdlib/stats/incr/mae`][@stdlib/stats/incr/mae]</span><span class="delimiter">: </span><span class="description">compute the mean absolute error (MAE) incrementally.</span>
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- <span class="package-name">[`@stdlib/stats/incr/mean`][@stdlib/stats/incr/mean]</span><span class="delimiter">: </span><span class="description">compute an arithmetic mean incrementally.</span>
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- <span class="package-name">[`@stdlib/stats/incr/mme`][@stdlib/stats/incr/mme]</span><span class="delimiter">: </span><span class="description">compute a moving mean error (ME) incrementally.</span>
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</section>
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<!-- /.related -->
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<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="links">
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[mean-absolute-error]: https://en.wikipedia.org/wiki/Mean_absolute_error
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<!-- <related-links> -->
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[@stdlib/stats/incr/mae]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mae
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[@stdlib/stats/incr/mean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mean
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[@stdlib/stats/incr/mme]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mme
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<!-- </related-links> -->
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</section>
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<!-- /.links -->

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

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var randu = require( '@stdlib/random/base/randu' );
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var pkg = require( './../package.json' ).name;
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var incrnanme = require( '@stdlib/stats/incr/nanme/lib' );
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// MAIN //
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bench( pkg, function benchmark( b ) {
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var f;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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f = incrnanme();
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if ( typeof f !== 'function' ) {
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b.fail( 'should return a function' );
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}
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}
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b.toc();
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if ( typeof f !== 'function' ) {
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b.fail( 'should return a function' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});
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bench( pkg+'::accumulator', function benchmark( b ) {
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var acc;
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var v;
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var i;
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acc = incrnanme();
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = acc( randu()-0.5, randu()-0.5 );
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if ( v !== v ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( v !== v ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});

‎lib/node_modules/@stdlib/stats/incr/nanme/docs/img/equation_mean_error.svg‎

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

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{{alias}}()
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Returns an accumulator function which incrementally computes the mean error
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(ME), ignoring NaN values.
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If provided input values, the accumulator function returns an updated mean
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error. If not provided input values, the accumulator function returns the
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current mean error.
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Returns
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-------
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acc: Function
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Accumulator function.
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Examples
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--------
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> var accumulator = {{alias}}();
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> var m = accumulator()
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null
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> m = accumulator( 2.0, 3.0 )
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1.0
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> m = accumulator( -5.0, 2.0 )
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4.0
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> m = accumulator( -3.0, NaN )
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4.0
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> m = accumulator( NaN, 2.0 )
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4.0
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> m = accumulator()
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4.0
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See Also
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--------
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‎lib/node_modules/@stdlib/stats/incr/nanme/docs/types/index.d.ts‎

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// TypeScript Version: 4.1
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/// <reference types="@stdlib/types"/>
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/**
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* 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.
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*
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* @param x - input value
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* @param y - input value
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* @returns mean error or null
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*/
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type accumulator = ( x?: number, y?: number ) => number | null;
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/**
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* Returns an accumulator function which incrementally computes the mean error, ignoring `NaN` values.
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*
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* @returns accumulator function
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*
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* @example
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* var accumulator = incrnanme();
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*
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* var m = accumulator();
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* // returns null
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*
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* m = accumulator( 2.0, 3.0 );
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* // returns 1.0
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*
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* m = accumulator( -5.0, 2.0 );
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* // returns 4.0
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*
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* m = accumulator( -3.0, NaN );
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* // returns 4.0
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*
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* m = accumulator( NaN, 2.0 );
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* // returns 4.0
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*
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* m = accumulator();
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* // returns 4.0
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*/
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declare function incrnanme(): accumulator;
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// EXPORTS //
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export = incrnanme;

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