# incrcv

Compute the coefficient of variation (CV) incrementally.

The corrected sample standard deviation is defined as

and the arithmetic mean is defined as

The coefficient of variation (also known as **relative standard deviation**, RSD) is defined as

## Usage

```
var incrcv = require( '@stdlib/stats/incr/cv' );
```

#### incrcv( [mean] )

Returns an accumulator `function`

which incrementally computes the coefficient of variation.

```
var accumulator = incrcv();
```

If the mean is already known, provide a `mean`

argument.

```
var accumulator = incrcv( 3.0 );
```

#### accumulator( [x] )

If provided an input value `x`

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

, the accumulator function returns the current accumulated value.

```
var accumulator = incrcv();
var cv = accumulator( 2.0 );
// returns 0.0
cv = accumulator( 1.0 ); // => s^2 = ((2-1.5)^2+(1-1.5)^2) / (2-1)
// returns ~0.47
cv = accumulator( 3.0 ); // => s^2 = ((2-2)^2+(1-2)^2+(3-2)^2) / (3-1)
// returns 0.5
cv = accumulator();
// returns 0.5
```

## 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. - The coefficient of variation is typically computed on nonnegative values. The measure may lack meaning for data which can assume both positive and negative values.
- For small and moderately sized samples, the accumulated value tends to be too low and is thus a
**biased**estimator. Provided the generating distribution is known (e.g., a normal distribution), you may want to adjust the accumulated value or use an alternative implementation providing an unbiased estimator.

## Examples

```
var randu = require( '@stdlib/random/base/randu' );
var incrcv = require( '@stdlib/stats/incr/cv' );
var accumulator;
var v;
var i;
// Initialize an accumulator:
accumulator = incrcv();
// For each simulated datum, update the coefficient of variation...
for ( i = 0; i < 100; i++ ) {
v = randu() * 100.0;
accumulator( v );
}
console.log( accumulator() );
```