# increwstdev

Compute an exponentially weighted standard deviation incrementally.

An exponentially weighted variance can be defined recursively as

where μ is the exponentially weighted mean. The exponentially weighted standard deviation is the square root of the exponentially weighted variance.

## Usage

var increwstdev = require( '@stdlib/stats/incr/ewstdev' );


#### increwstdev( alpha )

Returns an accumulator function which incrementally computes an exponentially weighted standard deviation, where alpha is a smoothing factor between 0 and 1.

var accumulator = increwstdev( 0.5 );


#### accumulator( [x] )

If provided an input value x, the accumulator function returns an updated standard deviation. If not provided an input value x, the accumulator function returns the current standard deviation.

var accumulator = increwstdev( 0.5 );

var s = accumulator();
// returns null

s = accumulator( 2.0 );
// returns 0.0

s = accumulator( 1.0 );
// returns 0.5

s = accumulator( 3.0 );
// returns ~0.83

s = accumulator();
// returns ~0.83


## 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

var randu = require( '@stdlib/random/base/randu' );
var increwstdev = require( '@stdlib/stats/incr/ewstdev' );

var accumulator;
var v;
var i;

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

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