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Compute an unbiased sample variance incrementally.
The unbiased sample variance is defined as
To use in Observable,
incrvariance = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-incr-variance@umd/browser.js' )To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var incrvariance = require( 'path/to/vendor/umd/stats-incr-variance/index.js' )To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-incr-variance@umd/browser.js"></script>If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.incrvariance;
})();
</script>Returns an accumulator function which incrementally computes an unbiased sample variance.
var accumulator = incrvariance();If the mean is already known, provide a mean argument.
var accumulator = incrvariance( 3.0 );If provided an input value x, the accumulator function returns an updated unbiased sample variance. If not provided an input value x, the accumulator function returns the current unbiased sample variance.
var accumulator = incrvariance();
var s2 = accumulator( 2.0 );
// returns 0.0
s2 = accumulator( 1.0 ); // => ((2-1.5)^2+(1-1.5)^2) / (2-1)
// returns 0.5
s2 = accumulator( 3.0 ); // => ((2-2)^2+(1-2)^2+(3-2)^2) / (3-1)
// returns 1.0
s2 = accumulator();
// returns 1.0- Input values are not type checked. If provided
NaNor a value which, when used in computations, results inNaN, the accumulated value isNaNfor 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.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-incr-variance@umd/browser.js"></script>
<script type="text/javascript">
(function () {
var accumulator;
var v;
var i;
// Initialize an accumulator:
accumulator = incrvariance();
// For each simulated datum, update the unbiased sample variance...
for ( i = 0; i < 100; i++ ) {
v = randu() * 100.0;
accumulator( v );
}
console.log( accumulator() );
})();
</script>
</body>
</html>@stdlib/stats-incr/kurtosis: compute a corrected sample excess kurtosis incrementally.@stdlib/stats-incr/mean: compute an arithmetic mean incrementally.@stdlib/stats-incr/mstdev: compute a moving corrected sample standard deviation incrementally.@stdlib/stats-incr/skewness: compute a corrected sample skewness incrementally.@stdlib/stats-incr/stdev: compute a corrected sample standard deviation incrementally.@stdlib/stats-incr/summary: compute a statistical summary incrementally.
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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