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feat(stats): add package nanmeanvar #6212

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231 changes: 231 additions & 0 deletions lib/node_modules/@stdlib/stats/incr/nanmeanvar/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.

-->

# incrnanmeanvar

> Compute an [arithmetic mean][arithmetic-mean] and an [unbiased sample variance][sample-variance] incrementally, ignoring `NaN` value.

<section class="intro">

The [arithmetic mean][arithmetic-mean] is defined as

<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> -->

```math
\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i
```

<!-- <div class="equation" align="center" data-raw-text="\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i" data-equation="eq:arithmetic_mean">
<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@b2df03cb2a582cf1df289c3ddca6922c0db854b4/lib/node_modules/@stdlib/stats/incr/meanvar/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
<br>
</div> -->

<!-- </equation> -->

and the [unbiased sample variance][sample-variance] is defined as

<!-- <equation class="equation" label="eq:unbiased_sample_variance" align="center" raw="s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2" alt="Equation for the unbiased sample variance."> -->

```math
s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2
```

<!-- <div class="equation" align="center" data-raw-text="s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2" data-equation="eq:unbiased_sample_variance">
<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eafa6e61d15b7c712c9288d59d8e0e3f0aa6c011/lib/node_modules/@stdlib/stats/incr/meanvar/docs/img/equation_unbiased_sample_variance.svg" alt="Equation for the unbiased sample variance.">
<br>
</div> -->

<!-- </equation> -->

<section class="usage">

## Usage

```javascript
var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' );
```

#### incrnanmeanvar( \[out] )

Returns an accumulator `function` which incrementally computes an [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance], ignoring `NaN` value.

```javascript
var accumulator = incrnanmeanvar();
```

By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object.

```javascript
var Float64Array = require( '@stdlib/array/float64' );

var accumulator = incrnanmeanvar( new Float64Array( 2 ) );
```

#### accumulator( \[x] )

If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values.

```javascript
var accumulator = incrnanmeanvar();

var mv = accumulator();
// returns null

mv = accumulator( 2.0 );
// returns [ 2.0, 0.0 ]

mv = accumulator( 1.0 );
// returns [ 1.5, 0.5 ]

mv = accumulator( 3.0 );
// returns [ 2.0, 1.0 ]

mv = accumulator( NaN );
// returns [ 2.0, 1.0 ]

mv = accumulator( -7.0 );
// returns [ -0.25, ~20.92 ]

mv = accumulator( -5.0 );
// returns [ -1.2, 20.2 ]

mv = accumulator();
// returns [ -1.2, 20.2 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- Input values are type checked; if a NaN value is provided, the accumulator skips the update and continues to return the previous state. If non-numeric inputs are possible, you are advised to type check and handle them accordingly **before** passing the value to the accumulator function.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var randu = require( '@stdlib/random/base/randu' );
var Float64Array = require( '@stdlib/array/float64' );
var ArrayBuffer = require( '@stdlib/array/buffer' );
var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' );

var offset;
var acc;
var buf;
var out;
var mv;
var N;
var v;
var i;
var j;

// Define the number of accumulators:
N = 5;

// Create an array buffer for storing accumulator output:
buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element

// Initialize accumulators:
acc = [];
for ( i = 0; i < N; i++ ) {
// Compute the byte offset:
offset = i * 2 * 8; // stride=2, bytes_per_element=8

// Create a new view for storing accumulated values:
out = new Float64Array( buf, offset, 2 );

// Initialize an accumulator which will write results to the view:
acc.push( incrnanmeanvar( out ) );
}

// Simulate data and update the sample means and variances...
for ( i = 0; i < 100; i++ ) {
for ( j = 0; j < N; j++ ) {
if ( randu() < 0.2 ) {
v = NaN;
} else {
v = randu() * 100.0 * (j+1);
}
acc[ j ]( v );
}
}

// Print the final results:
console.log( 'Mean\tVariance' );
for ( i = 0; i < N; i++ ) {
mv = acc[ i ]();
console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) );
}
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

- <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>
- <span class="package-name">[`@stdlib/stats/incr/meanstdev`][@stdlib/stats/incr/meanstdev]</span><span class="delimiter">: </span><span class="description">compute an arithmetic mean and corrected sample standard deviation incrementally.</span>
- <span class="package-name">[`@stdlib/stats/incr/mmeanvar`][@stdlib/stats/incr/mmeanvar]</span><span class="delimiter">: </span><span class="description">compute a moving arithmetic mean and unbiased sample variance incrementally.</span>
- <span class="package-name">[`@stdlib/stats/incr/variance`][@stdlib/stats/incr/variance]</span><span class="delimiter">: </span><span class="description">compute an unbiased sample variance incrementally.</span>

</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">

[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean

[sample-variance]: https://en.wikipedia.org/wiki/Variance

<!-- <related-links> -->

[@stdlib/stats/incr/mean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mean

[@stdlib/stats/incr/meanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/meanstdev

[@stdlib/stats/incr/mmeanvar]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mmeanvar

[@stdlib/stats/incr/variance]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/variance

<!-- </related-links> -->

</section>

<!-- /.links -->
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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 incrnanmeanvar = require( './../lib' );


// MAIN //

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

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = acc( randu() );
if ( v.length !== 2 ) {
b.fail( 'should contain two elements' );
}
}
b.toc();
if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
});
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