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161 changes: 161 additions & 0 deletions lib/node_modules/@stdlib/stats/incr/nanmmae/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.

-->

# incrnanmmae

> Compute a moving [mean absolute error][mean-absolute-error] (MAE) incrementally, ignoring `NaN` values.

<section class="intro">

For a window of size `W`, the [mean absolute error][mean-absolute-error] is defined as

<!-- <equation class="equation" label="eq:mean_absolute_error" align="center" raw="\operatorname{MAE} = \frac{1}{W} \sum_{i=0}^{W-1} |y_i - x_i|" alt="Equation for the mean absolute error."> -->

```math
\mathop{\mathrm{MAE}} = \frac{1}{W} \sum_{i=0}^{W-1} |y_i - x_i|
```

<!-- <div class="equation" align="center" data-raw-text="\operatorname{MAE} = \frac{1}{W} \sum_{i=0}^{W-1} |y_i - x_i|" data-equation="eq:mean_absolute_error">
<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@2fd94e331f96b2984303ca92fad16757cfc5fdcb/lib/node_modules/@stdlib/stats/incr/nanmmae/docs/img/equation_mean_absolute_error.svg" alt="Equation for the mean absolute error.">
<br>
</div> -->

<!-- </equation> -->

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var incrnanmmae = require( '@stdlib/stats/incr/nanmmae' );
```

#### incrnanmmae( window )

Returns an accumulator function which incrementally computes a moving [mean absolute error][mean-absolute-error]. The `window` parameter defines the number of values over which to compute the moving [mean absolute error][mean-absolute-error], ignoring `NaN` values.

```javascript
var accumulator = incrnanmmae( 3 );
```

#### accumulator( \[x, y] )

If provided input values `x` and `y`, the accumulator function returns an updated [mean absolute error][mean-absolute-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean absolute error][mean-absolute-error].

```javascript
var accumulator = incrnanmmae( 3 );

var m = accumulator();
// returns null

// Fill the window...
m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)]
// returns 1.0

m = accumulator( NaN, 2.0 );
// returns 1.0

m = accumulator( -5.0, NaN );
// returns 1.0

m = accumulator( -1.0, 4.0 ); // [(2.0,3.0), (-1.0,4.0)]
// returns 3.0

m = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (-1.0,4.0), (3.0,9.0)]
// returns 4.0

// Window begins sliding...
m = accumulator( -7.0, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)]
// returns 7.0

m = accumulator( -5.0, -3.0 ); // [(3.0,9.0), (-7.0,3.0), (-5.0,-3.0)]
// returns 6.0

m = accumulator();
// returns 6.0
```

</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` (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.
- **Warning**: the [mean absolute 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 uniform = require( '@stdlib/random/base/uniform' );
var bernoulli = require( '@stdlib/random/base/bernoulli' );
var incrnanmmae = require( '@stdlib/stats/incr/nanmmae' );

// Initialize an accumulator:
var accumulator = incrnanmmae( 5 );

// For each simulated datum, update the moving mean absolute error...
var v1;
var v2;
var i;
for ( i = 0; i < 100; i++ ) {
v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 );
v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 );
accumulator( v1, v2 );
}
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">

[mean-absolute-error]: https://en.wikipedia.org/wiki/Mean_absolute_error

</section>

<!-- /.links -->
69 changes: 69 additions & 0 deletions lib/node_modules/@stdlib/stats/incr/nanmmae/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 randu = require( '@stdlib/random/base/randu' );
var pkg = require( './../package.json' ).name;
var incrnanmmae = require( './../lib' );


// MAIN //

bench( pkg, function benchmark( b ) {
var f;
var i;
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
f = incrnanmmae( (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 = incrnanmmae( 5 );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
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();
});
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49 changes: 49 additions & 0 deletions lib/node_modules/@stdlib/stats/incr/nanmmae/docs/repl.txt
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{{alias}}( W )
Returns an accumulator function which incrementally computes a moving
mean absolute error (MAE), ignoring `NaN` values.

The `W` parameter defines the number of values over which to compute the
moving mean absolute error.

If provided a value, the accumulator function returns an updated moving
mean absolute error. If not provided a value, the accumulator function
returns the current moving mean absolute 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.

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( NaN, 2.0 )
1.0
> m = accumulator( -5.0, NaN )
1.0
> m = accumulator( -5.0, 2.0 )
4.0
> m = accumulator( 3.0, 2.0 )
3.0
> m = accumulator( 5.0, -2.0 )
5.0
> m = accumulator()
5.0

See Also
--------

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