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feat: add stats/incr/nanmpe
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‎lib/node_modules/@stdlib/stats/incr/nanmpe/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2026 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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# incrnanmpe
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> Compute the [mean percentage error][mean-percentage-error] (MPE) incrementally, ignoring `NaN` values.
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<section class="intro">
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The [mean percentage error][mean-percentage-error] is defined as
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<!-- <equation class="equation" label="eq:mean_percentage_error" align="center" raw="\operatorname{MPE} = \frac{100}{n} \sum_{i=0}^{n-1} \frac{a_i - f_i}{a_i}" alt="Equation for the mean percentage error."> -->
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```math
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\mathop{\mathrm{MPE}} = \frac{100}{n} \sum_{i=0}^{n-1} \frac{a_i - f_i}{a_i}
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```
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<!-- <div class="equation" align="center" data-raw-text="\operatorname{MPE} = \frac{100}{n} \sum_{i=0}^{n-1} \frac{a_i - f_i}{a_i}" data-equation="eq:mean_percentage_error">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@2acedf866c9a4f1353af22f95780535612c5ee06/lib/node_modules/@stdlib/stats/incr/nampe/docs/img/equation_mean_percentage_error.svg" alt="Equation for the mean percentage error.">
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<br>
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</div> -->
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<!-- </equation> -->
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where `f_i` is the forecast value and `a_i` is the actual value.
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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 incrnanmpe = require( '@stdlib/stats/incr/nanmpe' );
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```
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#### incrnanmpe()
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Returns an accumulator `function` which incrementally computes the [mean percentage error][mean-percentage-error], ignoring `NaN` values.
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```javascript
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var accumulator = incrnanmpe();
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```
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#### accumulator( \[f, a] )
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If provided input values `f` and `a`, the accumulator function returns an updated [mean percentage error][mean-percentage-error]. If not provided input values `f` and `a`, the accumulator function returns the current [mean percentage error][mean-percentage-error].
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```javascript
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var accumulator = incrnanmpe();
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var m = accumulator( 2.0, 3.0 );
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// returns ~33.33
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m = accumulator( NaN, 4.0 );
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// returns ~33.33
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m = accumulator( 1.0, 4.0 );
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// returns ~54.17
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m = accumulator( 3.0, NaN );
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// returns ~54.17
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m = accumulator( 3.0, 5.0 );
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// returns ~49.44
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m = accumulator();
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// returns ~49.44
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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 provided `NaN`, the accumulated value is `NaN` for **all** future invocations **until** a non-`NaN` value pair is provided. 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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- Note that if either `f` or `a` is `NaN`, the input value pair is **skipped** (i.e., the pair does not contribute to the accumulated value).
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- Be careful when interpreting the [mean percentage error][mean-percentage-error] as errors can cancel. This stated, that errors can cancel makes the [mean percentage error][mean-percentage-error] suitable for measuring the bias in forecasts.
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- **Warning**: the [mean percentage error][mean-percentage-error] is **not** suitable for intermittent demand patterns (i.e., when `a_i` is `0`). Interpretation is most straightforward when actual and forecast values are positive valued (e.g., number of widgets sold).
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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 bernoulli = require( '@stdlib/random/base/bernoulli' );
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var randu = require( '@stdlib/random/base/randu' );
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var incrnanmpe = require( '@stdlib/stats/incr/nanmpe' );
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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 = incrnanmpe();
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// For each simulated datum, update the mean percentage error...
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for ( i = 0; i < 100; i++ ) {
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v1 = ( bernoulli( 0.8 ) === 0 ) ? NaN : ( randu()*100.0 ) + 50.0;
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v2 = ( bernoulli( 0.8 ) === 0 ) ? NaN : ( randu()*100.0 ) + 50.0;
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accumulator( v1, v2 );
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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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</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-percentage-error]: https://en.wikipedia.org/wiki/Mean_percentage_error
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/stats/incr/nanmpe/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) 2026 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 incrnanmpe = require( './../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 = incrnanmpe();
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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 = incrnanmpe();
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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/nanmpe/docs/img/equation_mean_percentage_error.svg‎

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

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{{alias}}()
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Returns an accumulator function which incrementally computes the mean
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percentage error (MPE), ignoring `NaN` values.
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If provided input values, the accumulator function returns an updated mean
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percentage error. If not provided input values, the accumulator function
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returns the current mean percentage 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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~33.33
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> m = accumulator( 2.0, NaN )
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~33.33
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> m = accumulator( 5.0, 2.0 )
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~-58.33
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> m = accumulator()
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~-58.33
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See Also
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--------
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‎lib/node_modules/@stdlib/stats/incr/nanmpe/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) 2026 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 percentage error. If not provided input values, the accumulator function returns the current mean percentage error.
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*
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* ## Notes
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*
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* - If either `f` or `a` is `NaN`, the input value pair is skipped (i.e., the pair does not contribute to the accumulated value).
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*
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* @param f - input value (forecast)
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* @param a - input value (actual)
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* @returns mean percentage error or null
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*/
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type accumulator = ( f?: number, a?: number ) => number | null;
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/**
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* Returns an accumulator function which incrementally computes the mean percentage 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 = incrnanmpe();
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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 ~33.33
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*
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* m = accumulator( NaN, 5.0 );
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* // returns ~33.33
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*
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* m = accumulator( 5.0, 2.0 );
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* // returns ~-58.33
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*
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* m = accumulator();
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* // returns ~-58.33
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*/
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declare function incrnanmpe(): accumulator;
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// EXPORTS //
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export = incrnanmpe;

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