Skip to content

Create an iterator which iteratively computes a cumulative arithmetic mean of squared absolute values.

License

Notifications You must be signed in to change notification settings

stdlib-js/stats-iter-cumeanabs2

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

itercumeanabs2

NPM version Build Status Coverage Status

Create an iterator which iteratively computes a cumulative arithmetic mean of squared absolute values.

The cumulative arithmetic mean of squared absolute values is defined as

$$\bar{x}_n = \frac{1}{n} \sum_{i=0}^n x_i^2$$

Installation

npm install @stdlib/stats-iter-cumeanabs2

Alternatively,

  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var itercumeanabs2 = require( '@stdlib/stats-iter-cumeanabs2' );

itercumeanabs2( iterator )

Returns an iterator which iteratively computes a cumulative arithmetic mean of squared absolute values.

var array2iterator = require( '@stdlib/array-to-iterator' );

var arr = array2iterator( [ 2.0, 1.0, 3.0, -7.0, -5.0 ] );
var it = itercumeanabs2( arr );

var m = it.next().value;
// returns 4.0

m = it.next().value;
// returns 2.5

m = it.next().value;
// returns ~4.67

m = it.next().value;
// returns 15.75

m = it.next().value;
// returns 17.6

Notes

  • If an iterated value is non-numeric (including NaN), the function returns NaN for all future iterations. If non-numeric iterated values are possible, you are advised to provide an iterator which type checks and handles non-numeric values accordingly.

Examples

var runif = require( '@stdlib/random-iter-uniform' );
var itercumeanabs2 = require( '@stdlib/stats-iter-cumeanabs2' );

// Create an iterator for generating uniformly distributed pseudorandom numbers:
var rand = runif( -10.0, 10.0, {
    'seed': 1234,
    'iter': 100
});

// Create an iterator for iteratively computing a cumulative mean of squared absolute values:
var it = itercumeanabs2( rand );

// Perform manual iteration...
var v;
while ( true ) {
    v = it.next();
    if ( typeof v.value === 'number' ) {
        console.log( 'meanabs2: %d', v.value );
    }
    if ( v.done ) {
        break;
    }
}

See Also


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

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.