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Create an iterator which iteratively computes a cumulative arithmetic mean.
The cumulative arithmetic mean is defined as
npm install @stdlib/stats-iter-cumean
Alternatively,
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tag without installation and bundlers, use the ES Module available on theesm
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).
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var itercumean = require( '@stdlib/stats-iter-cumean' );
Returns an iterator which iteratively computes a cumulative arithmetic mean.
var array2iterator = require( '@stdlib/array-to-iterator' );
var arr = array2iterator( [ 2.0, 1.0, 3.0, -7.0, -5.0 ] );
var it = itercumean( arr );
var m = it.next().value;
// returns 2.0
m = it.next().value;
// returns 1.5
m = it.next().value;
// returns 2.0
m = it.next().value;
// returns -0.25
m = it.next().value;
// returns -1.2
- If an iterated value is non-numeric (including
NaN
), the function returnsNaN
for all future iterations. If non-numeric iterated values are possible, you are advised to provide aniterator
which type checks and handles non-numeric values accordingly.
var runif = require( '@stdlib/random-iter-uniform' );
var itercumean = require( '@stdlib/stats-iter-cumean' );
// 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:
var it = itercumean( rand );
// Perform manual iteration...
var v;
while ( true ) {
v = it.next();
if ( typeof v.value === 'number' ) {
console.log( 'mean: %d', v.value );
}
if ( v.done ) {
break;
}
}
@stdlib/stats-iter/cumidrange
: create an iterator which iteratively computes a cumulative mid-range.@stdlib/stats-iter/cusum
: create an iterator which iteratively computes a cumulative sum.@stdlib/stats-iter/mean
: compute the arithmetic mean over 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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