increwvariance

Compute an exponentially weighted variance incrementally.

An exponentially weighted variance can be defined recursively as

where μ is the exponentially weighted mean.

Installation

npm install @stdlib/stats-incr-ewvariance

Usage

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

increwvariance( alpha )

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

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.

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

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 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() );

See Also

• @stdlib/stats-incr/ewmean: compute an exponentially weighted mean incrementally.
• @stdlib/stats-incr/ewstdev: compute an exponentially weighted standard deviation incrementally.
• @stdlib/stats-incr/variance: compute an unbiased sample variance incrementally.
• @stdlib/stats-incr/mvariance: compute a moving unbiased sample variance incrementally.

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.