# incrmse
> Compute the [mean squared error][mean-squared-error] (MSE) incrementally.
The [mean squared error][mean-squared-error] is defined as
## Usage
```javascript
var incrmse = require( '@stdlib/stats/incr/mse' );
```
#### incrmse()
Returns an accumulator `function` which incrementally computes the [mean squared error][mean-squared-error].
```javascript
var accumulator = incrmse();
```
#### accumulator( \[x, y] )
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].
```javascript
var accumulator = incrmse();
var m = accumulator( 2.0, 3.0 );
// returns 1.0
m = accumulator( -1.0, -4.0 );
// returns 5.0
m = accumulator( -3.0, 5.0 );
// returns ~24.67
m = accumulator();
// returns ~24.67
```
## 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 incrmse = require( '@stdlib/stats/incr/mse' );
var accumulator;
var v1;
var v2;
var i;
// Initialize an accumulator:
accumulator = incrmse();
// For each simulated datum, update the mean squared error...
for ( i = 0; i < 100; i++ ) {
v1 = ( randu()*100.0 ) - 50.0;
v2 = ( randu()*100.0 ) - 50.0;
accumulator( v1, v2 );
}
console.log( accumulator() );
```
[mean-squared-error]: https://en.wikipedia.org/wiki/Mean_squared_error
