time-to-botec/squiggle/node_modules/@stdlib/stats/incr/ewvariance/README.md

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# increwvariance

> Compute an [exponentially weighted variance][moving-average] incrementally.

<section class="intro">

An [exponentially weighted variance][moving-average] can be defined recursively as

<!-- <equation class="equation" label="eq:exponentially_weighted_variance" align="center" raw="S_n = \begin{cases} 0 & \textrm{if}\ n = 0 \\ (1 - \alpha) (S_{n-1} + \alpha(x_n - \mu_{n-1})^2) & \textrm{if}\ n > 0 \end{cases}" alt="Recursive definition for computing an exponentially weighted variance."> -->

<div class="equation" align="center" data-raw-text="S_n = \begin{cases} 0 &amp; \textrm{if}\ n = 0 \\ (1 - \alpha) (S_{n-1} + \alpha(x_n - \mu_{n-1})^2) &amp; \textrm{if}\ n &gt; 0 \end{cases}" data-equation="eq:exponentially_weighted_variance">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@12be48682a7c25918504f886cbb80051c6ec8240/lib/node_modules/@stdlib/stats/incr/ewvariance/docs/img/equation_exponentially_weighted_variance.svg" alt="Recursive definition for computing an exponentially weighted variance.">
    <br>
</div>

<!-- </equation> -->

where `μ` is the [exponentially weighted mean][@stdlib/stats/incr/ewmean].

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var increwvariance = require( '@stdlib/stats/incr/ewvariance' );
```

#### increwvariance( alpha )

Returns an accumulator `function` which incrementally computes an [exponentially weighted variance][moving-average], where `alpha` is a smoothing factor between `0` and `1`.

```javascript
var accumulator = increwvariance( 0.5 );
```

#### accumulator( \[x] )

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

```javascript
var accumulator = increwvariance( 0.5 );

var v = accumulator();
// returns null

v = accumulator( 2.0 );
// returns 0.0

v = accumulator( 1.0 );
// returns 0.25

v = accumulator( 3.0 );
// returns 0.6875

v = accumulator();
// returns 0.6875
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for **all** future invocations. If non-numeric inputs are possible, you are advised to type check and handle 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 increwvariance = require( '@stdlib/stats/incr/ewvariance' );

var accumulator;
var v;
var i;

// Initialize an accumulator:
accumulator = increwvariance( 0.5 );

// For each simulated datum, update the exponentially weighted variance...
for ( i = 0; i < 100; i++ ) {
    v = randu() * 100.0;
    accumulator( v );
}
console.log( accumulator() );
```

</section>

<!-- /.examples -->

<section class="links">

[moving-average]: https://en.wikipedia.org/wiki/Moving_average

[@stdlib/stats/incr/ewmean]: https://www.npmjs.com/package/@stdlib/stats/tree/main/incr/ewmean

</section>

<!-- /.links -->