Compute the sum of squared absolute values for all iterated values.
APACHE-2.0 License
Compute the sum of squared absolute values for all iterated values.
The sum of squared absolute values is defined as
s = \sum_{i=0}^{n-1} x_i^2
npm install @stdlib/stats-iter-sumabs2
Alternatively,
script
tag without installation and bundlers, use the ES Module available on the esm
branch (see README).deno
branch (see README for usage intructions).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.
var itersumabs2 = require( '@stdlib/stats-iter-sumabs2' );
Computes the sum of squared absolute values for all iterated values.
var array2iterator = require( '@stdlib/array-to-iterator' );
var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );
var s = itersumabs2( arr );
// returns 30.0
NaN
), the returned iterator
returns NaN
. If non-numeric iterated values are possible, you are advised to provide an iterator
which type checks and handles non-numeric values accordingly.var runif = require( '@stdlib/random-iter-uniform' );
var itersumabs2 = require( '@stdlib/stats-iter-sumabs2' );
// Create an iterator for generating uniformly distributed pseudorandom numbers:
var rand = runif( -10.0, 10.0, {
'seed': 1234,
'iter': 100
});
// Compute the sum of squared absolute values:
var s = itersumabs2( rand );
// returns <number>
console.log( 'sumabs2: %d.', s );
@stdlib/stats-iter/meanabs2
: compute the arithmetic mean of squared absolute values for all iterated values.
@stdlib/stats-iter/msumabs2
: create an iterator which iteratively computes a moving sum of squared absolute values.
@stdlib/stats-iter/sumabs
: compute the sum of absolute values for all iterated values.
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.
See LICENSE.
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