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Compute the unbiased sample variance over all iterated values.
The unbiased sample variance is defined as
npm install @stdlib/stats-iter-variance
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
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umd
branch (see README).
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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 itervariance = require( '@stdlib/stats-iter-variance' );
Computes the unbiased sample variance over all iterated values.
var array2iterator = require( '@stdlib/array-to-iterator' );
var arr = array2iterator( [ 2.0, 1.0, 3.0 ] );
var s2 = itervariance( arr );
// returns 1.0
If the mean is already known, provide a mean
argument.
var array2iterator = require( '@stdlib/array-to-iterator' );
var arr = array2iterator( [ 2.0, 1.0, 3.0 ] );
var s2 = itervariance( arr, 2.0 );
// returns ~0.67
var runif = require( '@stdlib/random-iter-uniform' );
var itervariance = require( '@stdlib/stats-iter-variance' );
// Create an iterator for generating uniformly distributed pseudorandom numbers:
var rand = runif( -10.0, 10.0, {
'seed': 1234,
'iter': 100
});
// Compute the unbiased sample variance:
var s2 = itervariance( rand );
// returns <number>
console.log( 'Variance: %d.', s2 );
@stdlib/stats-iter/mean
: compute the arithmetic mean over all iterated values.@stdlib/stats-iter/stdev
: compute the corrected sample standard deviation 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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