0.2.1 • Published 3 months ago

@stdlib/stats-incr-stdev v0.2.1

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License
Apache-2.0
Repository
github
Last release
3 months ago

incrstdev

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Compute a corrected sample standard deviation incrementally.

The corrected sample standard deviation is defined as

Installation

npm install @stdlib/stats-incr-stdev

Usage

var incrstdev = require( '@stdlib/stats-incr-stdev' );

incrstdev( [mean] )

Returns an accumulator function which incrementally computes a corrected sample standard deviation.

var accumulator = incrstdev();

If the mean is already known, provide a mean argument.

var accumulator = incrstdev( 3.0 );

accumulator( [x] )

If provided an input value x, the accumulator function returns an updated corrected sample standard deviation. If not provided an input value x, the accumulator function returns the current corrected sample standard deviation.

var accumulator = incrstdev();

var s = accumulator( 2.0 );
// returns 0.0

s = accumulator( 1.0 ); // => sqrt(((2-1.5)^2+(1-1.5)^2) / (2-1))
// returns ~0.7071

s = accumulator( 3.0 ); // => sqrt(((2-2)^2+(1-2)^2+(3-2)^2) / (3-1))
// returns 1.0

s = accumulator();
// returns 1.0

Notes

  • Input values are not type checked. If provided NaN or a value which, when used in computations, results in NaN, the accumulated value is NaN for 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.

Examples

var randu = require( '@stdlib/random-base-randu' );
var incrstdev = require( '@stdlib/stats-incr-stdev' );

var accumulator;
var v;
var i;

// Initialize an accumulator:
accumulator = incrstdev();

// For each simulated datum, update the sample standard deviation...
for ( i = 0; i < 100; i++ ) {
    v = randu() * 100.0;
    accumulator( v );
}
console.log( accumulator() );

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.

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.