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feat: adding stats/incr/nanmmse
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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"); | ||
you may not use this file except in compliance with the License. | ||
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 | ||
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. | ||
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--> | ||
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# incrnanmmse | ||
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> Compute a moving [mean squared error][mean-squared-error] (MSE) incrementally, ignoring `NaN` values. | ||
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<section class="intro"> | ||
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For a window of size `W`, the [mean squared error][mean-squared-error] is defined as | ||
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<!-- <equation class="equation" label="eq:mean_squared_error" align="center" raw="\operatorname{MSE} = \frac{1}{W} \sum_{i=0}^{W-1} (y_i - x_i)^2" alt="Equation for the mean squared error."> --> | ||
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```math | ||
\mathop{\mathrm{MSE}} = \frac{1}{W} \sum_{i=0}^{W-1} (y_i - x_i)^2 | ||
``` | ||
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<!-- <div class="equation" align="center" data-raw-text="\operatorname{MSE} = \frac{1}{W} \sum_{i=0}^{W-1} (y_i - x_i)^2" data-equation="eq:mean_squared_error"> | ||
<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@9cb3c4a2fcf92ca07ed60c34de1ceda40f75919c/lib/node_modules/@stdlib/stats/incr/nanmmse/docs/img/equation_mean_squared_error.svg" alt="Equation for the mean squared error."> | ||
<br> | ||
</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 | ||
var incrnanmmse = require( '@stdlib/stats/incr/nanmmse' ); | ||
``` | ||
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#### incrnanmmse( window ) | ||
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Returns an accumulator `function` which incrementally computes a moving [mean squared error][mean-squared-error]. The `window` parameter defines the number of values over which to compute the moving [mean squared error][mean-squared-error]. | ||
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```javascript | ||
var accumulator = incrnanmmse( 3 ); | ||
``` | ||
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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 squared error][mean-squared-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean squared error][mean-squared-error]. | ||
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```javascript | ||
var accumulator = incrnanmmse( 3 ); | ||
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var m = accumulator(); | ||
// returns null | ||
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// Fill the window... | ||
m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)] | ||
// returns 1.0 | ||
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m = accumulator( -1.0, 4.0 ); // [(2.0,3.0), (-1.0,4.0)] | ||
// returns 13.0 | ||
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m = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (-1.0,4.0), (3.0,9.0)] | ||
// returns ~20.67 | ||
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// Window begins sliding... | ||
m = accumulator( -7.0, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)] | ||
// returns ~53.67 | ||
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m = accumulator( NaN, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)] | ||
// returns ~53.67 | ||
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m = accumulator( -5.0, -3.0 ); // [(3.0,9.0), (-7.0,3.0), (-5.0,-3.0)] | ||
// returns ~46.67 | ||
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m = accumulator(); | ||
// returns ~46.67 | ||
``` | ||
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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. | ||
- 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. | ||
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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 | ||
var randu = require( '@stdlib/random/base/randu' ); | ||
var incrnanmmse = require( '@stdlib/stats/incr/nanmmse' ); | ||
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var accumulator; | ||
var v1; | ||
var v2; | ||
var i; | ||
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// Initialize an accumulator: | ||
accumulator = incrnanmmse( 5 ); | ||
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// For each simulated datum, update the moving mean squared error... | ||
for ( i = 0; i < 100; i++ ) { | ||
if ( randu() < 0.2 ) { | ||
v1 = NaN; | ||
v2 = NaN; | ||
} else { | ||
v1 = ( randu()*100.0 ) - 50.0; | ||
v2 = ( randu()*100.0 ) - 50.0; | ||
} | ||
accumulator( v1, v2 ); | ||
} | ||
console.log( accumulator() ); | ||
``` | ||
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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/mrmse`][@stdlib/stats/incr/mrmse]</span><span class="delimiter">: </span><span class="description">compute a moving root mean squared error (RMSE) incrementally.</span> | ||
- <span class="package-name">[`@stdlib/stats/incr/mrss`][@stdlib/stats/incr/mrss]</span><span class="delimiter">: </span><span class="description">compute a moving residual sum of squares (RSS) incrementally.</span> | ||
- <span class="package-name">[`@stdlib/stats/incr/mse`][@stdlib/stats/incr/mse]</span><span class="delimiter">: </span><span class="description">compute the mean squared error (MSE) 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-squared-error]: https://en.wikipedia.org/wiki/Mean_squared_error | ||
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<!-- <related-links> --> | ||
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[@stdlib/stats/incr/mrmse]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mrmse | ||
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[@stdlib/stats/incr/mrss]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mrss | ||
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[@stdlib/stats/incr/mse]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mse | ||
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<!-- </related-links> --> | ||
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</section> | ||
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<!-- /.links --> |
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69
lib/node_modules/@stdlib/stats/incr/nanmmse/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. | ||
*/ | ||
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'use strict'; | ||
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// MODULES // | ||
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var bench = require( '@stdlib/bench' ); | ||
var randu = require( '@stdlib/random/base/randu' ); | ||
var pkg = require( './../package.json' ).name; | ||
var incrnanmmse = require( './../lib' ); | ||
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// MAIN // | ||
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bench( pkg, function benchmark( b ) { | ||
var f; | ||
var i; | ||
b.tic(); | ||
for ( i = 0; i < b.iterations; i++ ) { | ||
f = incrnanmmse( (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(); | ||
}); | ||
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bench( pkg+'::accumulator', function benchmark( b ) { | ||
var acc; | ||
var v; | ||
var i; | ||
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acc = incrnanmmse( 5 ); | ||
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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(); | ||
}); |
60 changes: 60 additions & 0 deletions
60
...ode_modules/@stdlib/stats/incr/nanmmse/docs/img/equation_mean_squared_error.svg
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{{alias}}( W ) | ||
Returns an accumulator function which incrementally computes a moving mean | ||
squared error (MSE), ignoring `NaN` values. | ||
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The `W` parameter defines the number of values over which to compute the | ||
moving mean squared error. | ||
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If provided a value, the accumulator function returns an updated moving mean | ||
squared error. If not provided a value, the accumulator function returns the | ||
current moving mean squared error. | ||
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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. | ||
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Parameters | ||
---------- | ||
W: integer | ||
Window size. | ||
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Returns | ||
------- | ||
acc: Function | ||
Accumulator function. | ||
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Examples | ||
-------- | ||
> var accumulator = {{alias}}( 3 ); | ||
> var m = accumulator() | ||
null | ||
> m = accumulator( 2.0, 3.0 ) | ||
1.0 | ||
> m = accumulator( -5.0, 2.0 ) | ||
25.0 | ||
> m = accumulator( NaN, 2.0 ) | ||
25.0 | ||
> m = accumulator( 3.0, 2.0 ) | ||
17.0 | ||
> m = accumulator( 3.0, NaN ) | ||
17.0 | ||
> m = accumulator( 5.0, -2.0 ) | ||
33.0 | ||
> m = accumulator() | ||
33.0 | ||
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See Also | ||
-------- | ||
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