# incrvariance
> Compute an [unbiased sample variance][sample-variance] incrementally.
The [unbiased sample variance][sample-variance] is defined as
## Usage
```javascript
var incrvariance = require( '@stdlib/stats/incr/variance' );
```
#### incrvariance( \[mean] )
Returns an accumulator `function` which incrementally computes an [unbiased sample variance][sample-variance].
```javascript
var accumulator = incrvariance();
```
If the mean is already known, provide a `mean` argument.
```javascript
var accumulator = incrvariance( 3.0 );
```
#### accumulator( \[x] )
If provided an input value `x`, the accumulator function returns an updated [unbiased sample variance][sample-variance]. If not provided an input value `x`, the accumulator function returns the current [unbiased sample variance][sample-variance].
```javascript
var accumulator = incrvariance();
var s2 = accumulator( 2.0 );
// returns 0.0
s2 = accumulator( 1.0 ); // => ((2-1.5)^2+(1-1.5)^2) / (2-1)
// returns 0.5
s2 = accumulator( 3.0 ); // => ((2-2)^2+(1-2)^2+(3-2)^2) / (3-1)
// returns 1.0
s2 = accumulator();
// returns 1.0
```
## 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.
## Examples
```javascript
var randu = require( '@stdlib/random/base/randu' );
var incrvariance = require( '@stdlib/stats/incr/variance' );
var accumulator;
var v;
var i;
// Initialize an accumulator:
accumulator = incrvariance();
// For each simulated datum, update the unbiased sample variance...
for ( i = 0; i < 100; i++ ) {
v = randu() * 100.0;
accumulator( v );
}
console.log( accumulator() );
```
[sample-variance]: https://en.wikipedia.org/wiki/Variance
